Entrées bibtex de la base bibliographique

@InProceedings{brun-00-2,


author = {Luc {B}run and Myriam Mokhtari},
title = {Two High Speed Color Quantization Algorithms},
booktitle = {Proceedings of CGIP'2000},
pages = {116-121},
year = 2000,
editor = {C{'e}padu{`e}s},
address = {Saint Etienne},
month = {October},
url = {article (.ps):=https://brunl01.users.greyc.fr/ARTICLES/cgip.ps, slides(PPT):=https://brunl01.users.greyc.fr/ARTICLES/cgip.ppt},
abstract = " Color image quantization has been widely
studied for the last fifteen years. Most of
existing quantization algorithms use pure
top-down or bottom-up approaches, in this
paper we present a two-pass quantization
method using a split stage followed by a merge
one. The split stage uses a uniform
quantization algorithm to generate $N$ initial
clusters. These clusters are then combined
during the merge stage into $K<<N$ final
clusters. Finally, these clusters are used by
an inverse colormap algorithm to create the
output image. Two different inverse colormap
algorithms are proposed leading to two
quantization algorithms. These quantization
algorithms are more efficient than pure split
or pure merge algorithms. Moreover, the
difference between the number of clusters
produced by the split stage and the number of
final clusters allows users to control
efficiently the quality/time ratio.",
theme={quantification}

 }

@InBook{brun-02,


author = {Luc {B}run and Alain Tr{'e}meau},
title = {Digital Color Imaging Handbook},
chapter = {9 : Color quantization},
pages = {589-637},
publisher = {CRC Press},
year = 2002,
theme = {quantification,couleur},
series = {Electrical and Applied Signal Processing},
url= {ResearchGate:=https://www.researchgate.net/publication/229476136_Digital_Color_Imaging_Handbook}

 }

@Unpublished{brun-02-8,


author = {Luc Brun},
title = {Traitement d'images couleur},
year = 2002,
url = {link to my lectures := https://brunl01.users.greyc.fr/ENSEIGNEMENT/enseignement.html},
theme = {couleur}

 }

@InProceedings{brun-97-3,


author = {Luc {B}run and Claude Secroun},
title = {Une nouvelle m{'e}thode d'inversion de tables de couleurs},
booktitle = {journ{'e}es de l'association francc{a}ise
d'informatique graphique },
year = 1997,
address = {Rennes},
theme = {inverse},
organization = {A.F.I.G.},
url= {article(.ps):=https://brunl01.users.greyc.fr/ARTICLES/afig97.ps.gz},
abstract = "L'inversion de la table de couleurs est un processus
permettant de cr{'e}er une image {`a} partir d'une
image d'entr{'e}e et d'un ensemble de couleurs
appel{'e} la table de couleurs ou l'ensemble des
couleurs repr{'e}sentatives. Afin de diminuer la
distance visuelle entre l'image d'entr{'e}e et l'image
r{'e}sultat, ce processus affecte {`a} chaque couleur
de l'image originale sa couleur la plus proche dans
la table de couleurs. La m{'e}thode que nous allons
pr{'e}senter est bas{'e}e sur une projection de
l'ensemble des couleurs de l'image sur un plan
discret. L'utilisation de ce plan nous permet
d'approximer efficacement le diagramme de Voronoi 3D
sous-jacent aux m{'e}thodes d'inversion de table de
couleurs."

 }

@Article{brun-99,


author = {Luc {B}run and Claude Secroun},
title = {A fast algorithm for inverse color map computation},
journal = {Computer Graphics Forum},
year = 1998,
volume = 17,
number = 4,
pages = {263-271},
theme = {inverse},
month = {December},
url = {article:=https://brunl01.users.greyc.fr/cgf.ps.gz},
abstract = "The inverse colormap operation is the process
which allows an image to be displayed with a
limited set of colors. In order to obtain minimal
visual distortion between the input image and the
displayed image, inverse colormap algorithms
associate each color with its nearest
representative. The method presented in this paper
is based on a Karhunen-Lo{`e}ve transformation,
which allows us to efficiently approximate the 3D
Voronoi diagram implicitly used by inverse color
map algorithms by its 2D projection into the plane
defined by the first two eigenvectors of the
covariance matrix and then performing an
additional correction step. The complexity of our
algorithm is independent of the size of the
colormap. Moreover, its results are equal or quite
close to the optimal solution."

 }

@InProceedings{hussenet-02-1,


author = {Laurent Hussenet and Luc Brun},
title = {Reconstruction of Shiny objects},
booktitle = {Proceedings of the International Conference on Computer Vision and Graphics},
pages = {337-342},
year = 2002,
editor = {Konrad Wojciechowseki},
address = {Zakopane, Poland},
month = {September},
theme = {couleur}

 }

@InProceedings{hussenet-01,


author = {Laurent Hussenet and Luc {B}run},
title = {Physic Based Classification for Color Images},
booktitle = {Physics in Signal & Image Processing},
pages = {173-176},
year = 2001,
address = {Marseille},
month = {January},
organization = {Soci{'e}t{'e} de l'{'E}lectricit{'e}, de l'{'E}lectronique et des Technologies de l'Information et de la Communication},
url= {article :=https://brunl01.users.greyc.fr/ARTICLES/psip_final.pdf},
abstract = " This paper presents a new method for segmenting color
images into regions composed of an unique
material. This method is based on a spectral
reflection model and a characterization of the camera
used for acquisitions. The study of these crucial
points of the acquisition process allows us to define
expressions which remain constants for all pixels's
color corresponding to a same material. These
constants are then used in the color segmentation
process.",
theme= {couleur}

 }

@InProceedings{braquelaire-94-1,


author = "Braquelaire, Jean Pierre and Luc Brun",
title = "Une am{'e}lioration des m{'e}thodes de quantification de
couleur par partition dynamique",
pages = "247-261",
booktitle = "Deuxi{`e}mes journ{'e}es de l'association francc{a}ise
d'informatique graphique ",
year = 1994,
organization = "A.F.I.G",
address = "Toulouse",
theme = {quantification},
abstract = "La quantification de couleurs est un probl{`e}me qui
bien qu'il admette d'autres applications a pris de
plus en plus d'importance au fur et {`a} mesure du
d{'e}veloppement des {'e}crans couleurs. Ce papier se
propose de revoir les principes des techniques de
quantification par partitionnement. Nous d{'e}gagerons
de ceux-ci quelques id{'e}es fortes qui nous
permettront de proposer un nouvel algorithme qui, s'
inscrivant dans la continuit{'e} des algorithmes
d{'e}j{`a} d{'e}velopp{'e}s, affiche des performances tant
en qualit{'e} qu'en espace m{'e}moire et temps de calcul
tout {`a} fait int{'e}ressantes."

 }

@InProceedings{braquelaire-95-1,


author = "Braquelaire, Jean Pierre and Luc Brun",
title = "Quantification de couleurs par partition dynamique",
booktitle = "Actes de la journ{'e}e Couleur et Informatique Graphique",
year = 1995,
address = "Lille ",
month = "Mars",
url = {article(.ps.gz):=https://brunl01.users.greyc.fr/ARTICLES/articleLILLE.ps.gz},
theme = {quantification},
abstract = "La quantification de couleurs est un probl{`e}me qui
bien qu'il admette d'autres applications a pris de
plus en plus d'importance au fur et {`a} mesure du
d{'e}veloppement des {'e}crans couleurs. Nous proposons
dans ce papier diverses am{'e}liorations des
algorithmes de type partitionement dynamique
permettant de diminuer l'erreur de quantification et
de r{'e}duire l'occupation m{'e}moire."

 }

@Article{braquelaire-97,


author = "Braquelaire, Jean Pierre. and Luc Brun",
title = "Comparison and Optimization of Methods of Color
Image Quantization",
journal = "IEEE Transactions on Image Processing",
year = 1997,
volume = 6,
number = 7,
pages = "1048-1052",
month = "july",
url= {article(.ps.gz) :=https://brunl01.users.greyc.fr/ARTICLES/articleIEEE.ps.gz, article(.ps) :=https://brunl01.users.greyc.fr/ARTICLES/articleIEEE.ps.gz},
theme= {quantification},
abstract = "Color image quantization is the process of reducing
the number of colors in a digital color image has
been widely studied for the last fifteen years. In
this paper the different steps of clustering methods
are studied. The methods are compared step by step
and some optimizations of the algorithms and data
structures are given. A new color space called
$H1H2H3$ is introduced which improves quantization
heuristics. A low-cost quantization scheme is
proposed."

 }

@Article{RI-ASSEMLAL-2011,


author = {Haz-Edine Assemlal and David Tschumperle and Luc Brun and Kaleem Siddiqi},
title = {Recent advances in diffusion MRI modeling: Angular and radial reconstruction},
journal = {Medical image analysis},
year = 2011,
volume = 15,
number = 4,
pages = {369-396},
month = {August},
theme = {misc},
url={pdf:=https://tschumperle.users.greyc.fr/publications/tschumperle_media11.pdf},
abstract="The analysis of the diffusion signal is closely related to
the sampling of the q-space. (a) Full sampling of
the q-space is currently impractical in vivo due to
the significant acquisition time it would imply. (b)
Low angular resolution sampling used in DTI. (c)
High angular resolution sampling (HARDI). (d) Radial
only sampling used in diffusion NMR. (e) Sparse
sampling which combines radial and angular
measurements. amants.mp3 amants.ogg annuaire_fichiers Audiobooks BIBTEX2XML bin Bureau COURRIER CYBELE DIVERS Documents Downloads Dropbox Enregistrements ENSEIGNEMENT f.c f.c~ flexdock Handout.ps hors_classe_carriere_2.pdf hors_classe_carriere_.pdf Hubic Images include kdenlive LATEX lib LouisePDA md5 ModÃ¨les Movies MUSIQUES my_f ogg ownCloud ownCloud2 passwords passwords~ PeerTV PETITS_PGRS Photos Podcasts preupgrade preupgrade-adobe-linux-i386 preupgrade-fedora preupgrade-google-chrome preupgrade-livna preupgrade-main preupgrade-rpmfusion-free preupgrade-rpmfusion-free-updates preupgrade-rpmfusion-nonfree preupgrade-rpmfusion-nonfree-updates preupgrade-updates Public public_html renov.pdf snapshot SpringLobby TÃ©lÃ©chargement tmp TNI tor-browser_en-US TRAVAIL Ubuntu One VidÃ©os vlc.playlist workspace x2-demo Acquisition time for a diffusion
image at full resolution is approximately 1h. amants.mp3 amants.ogg annuaire_fichiers Audiobooks BIBTEX2XML bin Bureau COURRIER CYBELE DIVERS Documents Downloads Dropbox Enregistrements ENSEIGNEMENT f.c f.c~ flexdock Handout.ps hors_classe_carriere_2.pdf hors_classe_carriere_.pdf Hubic Images include kdenlive LATEX lib LouisePDA md5 ModÃ¨les Movies MUSIQUES my_f ogg ownCloud ownCloud2 passwords passwords~ PeerTV PETITS_PGRS Photos Podcasts preupgrade preupgrade-adobe-linux-i386 preupgrade-fedora preupgrade-google-chrome preupgrade-livna preupgrade-main preupgrade-rpmfusion-free preupgrade-rpmfusion-free-updates preupgrade-rpmfusion-nonfree preupgrade-rpmfusion-nonfree-updates preupgrade-updates Public public_html renov.pdf snapshot SpringLobby TÃ©lÃ©chargement tmp TNI tor-browser_en-US TRAVAIL Ubuntu One VidÃ©os vlc.playlist workspace x2-demo
Direct processing of the data is not reliable due to
the limited number of samples. amants.mp3 amants.ogg annuaire_fichiers Audiobooks BIBTEX2XML bin Bureau COURRIER CYBELE DIVERS Documents Downloads Dropbox Enregistrements ENSEIGNEMENT f.c f.c~ flexdock Handout.ps hors_classe_carriere_2.pdf hors_classe_carriere_.pdf Hubic Images include kdenlive LATEX lib LouisePDA md5 ModÃ¨les Movies MUSIQUES my_f ogg ownCloud ownCloud2 passwords passwords~ PeerTV PETITS_PGRS Photos Podcasts preupgrade preupgrade-adobe-linux-i386 preupgrade-fedora preupgrade-google-chrome preupgrade-livna preupgrade-main preupgrade-rpmfusion-free preupgrade-rpmfusion-free-updates preupgrade-rpmfusion-nonfree preupgrade-rpmfusion-nonfree-updates preupgrade-updates Public public_html renov.pdf snapshot SpringLobby TÃ©lÃ©chargement tmp TNI tor-browser_en-US TRAVAIL Ubuntu One VidÃ©os vlc.playlist workspace x2-demo Numerous
reconstruction models of the literature are
described in this review. amants.mp3 amants.ogg annuaire_fichiers Audiobooks BIBTEX2XML bin Bureau COURRIER CYBELE DIVERS Documents Downloads Dropbox Enregistrements ENSEIGNEMENT f.c f.c~ flexdock Handout.ps hors_classe_carriere_2.pdf hors_classe_carriere_.pdf Hubic Images include kdenlive LATEX lib LouisePDA md5 ModÃ¨les Movies MUSIQUES my_f ogg ownCloud ownCloud2 passwords passwords~ PeerTV PETITS_PGRS Photos Podcasts preupgrade preupgrade-adobe-linux-i386 preupgrade-fedora preupgrade-google-chrome preupgrade-livna preupgrade-main preupgrade-rpmfusion-free preupgrade-rpmfusion-free-updates preupgrade-rpmfusion-nonfree preupgrade-rpmfusion-nonfree-updates preupgrade-updates Public public_html renov.pdf snapshot SpringLobby TÃ©lÃ©chargement tmp TNI tor-browser_en-US TRAVAIL Ubuntu One VidÃ©os vlc.playlist workspace x2-demo Three groups of methods
based on the nature of sampling: angular, radial and
combined. Recent advances in diffusion magnetic
resonance image (dMRI) modeling have led to the
development of several state of the art methods for
reconstructing the diffusion signal. These methods
allow for distinct features to be computed, which in
turn reflect properties of fibrous tissue in the
brain and in other organs. A practical consideration
is that to choose among these approaches requires
very specialized knowledge. In order to bridge the
gap between theory and practice in dMRI
reconstruction and analysis we present a detailed
review of the dMRI modeling literature. We place an
emphasis on the mathematical and algorithmic
underpinnings of the subject, categorizing existing
methods according to how they treat the angular and
radial sampling of the diffusion signal. We describe
the features that can be computed with each method
and discuss its advantages and limitations. We also
provide a detailed bibliography to guide the
reader."

 }

@InProceedings{CI-TSCHUMPERLE-2008-1,


author = {Tschumperl{'e}, D. and Brun, L.},
title = {Image Denoising and Registration by PDE's on the Space of Patches},
booktitle = {International Workshop on Local and Non-Local Approximation in Image Processing (LNLA'08)},
pages = {} ,
year = {2008},
theme = {misc},
address = {Lausanne},
url={HAL:= http://hal.archives-ouvertes.fr/hal-00332804, pdf := http://hal.archives-ouvertes.fr/docs/00/33/28/04/PDF/tschumperle_brun_lnla2008.pdf}

 }

@TechReport{TR-TSCHUMPERLE-2008,


author = {Tschumperl{'e}, D. and Brun, L.},
title = {Defining Some Variational Methods on the Space of Patches : Application to Multi-Valued Image Denoising and Registration},
institution = {GREYC},
year = 2008,
number = {08/01},
theme = {misc}

 }

@TechReport{TR-Assemlal-2007,


author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun},
title = {A Variational Framework for the Robust Estimation of ODFs From High Angular Resolution Diffusion Images.},
institution = {GREYC},
year = 2007,
number = {07-01},
month = {April},
theme = {misc},
url= {pdf :=http://www.greyc.ensicaen.fr/~dtschump/data/cahier_greyc07-01.pdf}


 }

@InProceedings{CI-Assemlal-2007,


author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun},
title = {Fiber Tracking on HARDI Data Using Robust ODF Fields.},
booktitle = {ICIP'2007, IEEE International Conference on Image Processing},
year = 2007,
address = {San Antonio/USA},
month = {September},
theme = {misc},
abstract= "We present a robust method to retrieve neuronal
fibers in human brain w hite matter from High-Angular
Resolution MRI (HARDI datasets). Contrary to class
ical fiber-tracking techniques done on the
traditional 2nd-order tensor model (D TI) which may
lead to truncated or biased estimated diffusion
directions in case of fiber crossing configurations,
we propose here a more complex approach based on a
variational estimation of Orientation Diffusion
Functions (ODF) modeled wi th spherical
harmonics. This kind of model can correctly retrieve
multiple fiber directions corresponding to underlying
intra-voxel fibers populations. Our tech nique is
able to consider the Rician noise model of the MRI
acquisition in order to better estimate the white
matter fiber tracks. Results on both synthetic and
real human brain white matter HARDI datasets
illustrate the effectiveness of th e proposed
approach.",
url={HAL:= http://hal.archives-ouvertes.fr/hal-00250226, pdf:=http://hal.archives-ouvertes.fr/docs/00/25/02/26/PDF/conf_icip2007_review.pdf, ps:=http://hal.archives-ouvertes.fr/docs/00/25/02/26/PS/conf_icip2007_review.ps, presentation:=https://brunl01.users.greyc.fr/ARTICLES/icip07_presentation.pdf}

 }

@InProceedings{CN-Assemlal-2007,


author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun},
title = {Estimation variationnelle robuste de mod{`e}les complexes de diffusion en IRM {`a} haute r{'e}solution angulaire et tractographie.},
booktitle = {GRETSI'2007},
year = 2007,
address = {Troyes/France},
month = {September},
theme = {misc},
abstract= "We present a robust method to retrieve neuronal
fibers in human brain white matter from High-Angular
Resolution MRI (HARDI datasets). Contrary to
classical fiber-tracking techniques done on the
traditional 2nd-order tensor model (DTI) which may
lead to truncated or biased estimated diffusion
directions in case of fiber crossing configurations,
we propose here a more complex approach based on a
variational estimation of Orientation Diffusion
Functions (ODF) modeled with spherical
harmonics. This kind of model can correctly retrieve
multiple fiber directions corresponding to underlying
intravoxel fibers populations. Our technique is able
to consider the Rician noise model of the MRI
acquisition in order to better estimate the white
matter fiber tracks. Results on both synthetic and
real human brain white matter HARDI datasets
illustrate the effectiveness of the proposed
approach.",
url={HAL := http://hal.archives-ouvertes.fr/hal-00329157, pdf:=http://hal.archives-ouvertes.fr/docs/00/32/91/57/PDF/gretsi07_publi.pdf,presentation:=https://brunl01.users.greyc.fr/ARTICLES/gretsi07_presentation.pdf}

 }

@article{assemlal09,


author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun},
title = {Efficient and Robust Computation of PDF Features from Diffusion MR Signal},
journal = {Medical Image Analysis},
year = {2009},
volume=13,
number=5,
pages={715-729},
abstract=" We present a method for the estimation of various features
of the tissue micro-architecture using the diffusion
magnetic resonance imaging. The considered features are
designed from the displacement probability density
function (PDF). The estimation is based on two steps:
first the approximation of the signal by a series
expansion made of Gaussian-Laguerre and Spherical
Harmonics functions; followed by a projection on a finite
dimensional space. Besides, we propose to tackle the
problem of the robustness to Rician noise corrupting
emphin-vivo acquisitions. Our feature estimation is
expressed as a variational minimization process leading to
a variational framework which is robust to noise. This
approach is very flexible regarding the number of samples
and enables the computation of a large set of various
features of the local tissues structure. We demonstrate
the effectiveness of the method with results on both
synthetic phantom and real MR datasets acquired in a
clinical time-frame.",
url={ HAL := http://hal.archives-ouvertes.fr/hal-00410615, pdf:=http://hal.archives-ouvertes.fr/docs/00/41/06/15/PDF/assemlal_MedIA09.pdf}


 }

@InProceedings{assemlal09-1,


author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun},
title = {Estimation de caractÃ©ristiques quelconques de la PDF Ã  partir d'un signal IRM de diffusion},
booktitle = {GRETSI},
year = 2009,
address = {Dijon,France},
month = {September},
theme = {misc}

 }

@InProceedings{assemlal09-2,


author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun},
title = {Evaluation of q-Space Sampling Strategies for the Diffusion Magnetic Resonance Imaging},
booktitle = {MICCAI},
year = 2009,
address = {London/England},
month = {September},
theme = {misc},
abstract="We address the problem of efficient sampling of the
diffusion space for the Diffusion Magnetic Resonance Imaging (dMRI)
modality. While recent scanner improvements enable the acquisition of
more and more detailed images, it is still unclear which q-space
sampling strategy gives the best performance. We evaluate several
q-space sampling distributions by an approach based on the
approximation of the MR signal by a series expansion of Spherical
Harmonics and Laguerre-Gaussian functions. With the help of synthetic
experiments, we identify a subset of sampling distributions which
leads to the best reconstructed data."

 }

@InProceedings{assemlal08,


author = {Assemlal, H-E. and David Tschumperl{'e} and Luc Brun},
title = {Robust Variational Estimation of PDF functions from Diffusion MR Signal.},
booktitle = {CDMRI},
year = 2008,
address = {New York/USA},
month = {September},
theme = {misc},
abstract="We address the problem of robust estimation of tissue
microstructure from Diffusion Magnetic Resonance Imaging (dMRI). On
one hand, recent hardware improvements enable the acquisition of more
detailed images, on the other hand, this comes along with a low Signal
to Noise (SNR) ratio. In such a context, the approximation of the
Rician acquisition noise as Gaussian is not accurate. We propose to
estimate the volume of PDF-based characteristics from data samples by
minimizing a nonlinear energy functional which considers Rician MR
acquisition noise as well as additional spatial regularity
constraints. This approach relies on the approximation of the MR
signal by a series expansion based on Spherical Harmonics and
Laguerre-Gaussian functions. Results are presented to depict the
performance of this PDE-based approach on synthetic data and human
brain data sets respectively.",
url={HAL:=http://hal.archives-ouvertes.fr/hal-00329263, pdf:=http://hal.archives-ouvertes.fr/docs/00/32/92/63/PDF/cdmri08.pdf, Presentation:=https://brunl01.users.greyc.fr/ARTICLES/cdmri08-2.pdf}

 }

@inproceedings{assemlal08-1,


author = {Assemlal, Haz-Edine and Tschumperl'e, David and Brun, Luc},
title = {Efficient Computation of PDF-Based Characteristics from Diffusion MR Signal},
booktitle = {MICCAI '08: Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II},
year = {2008},
isbn = {978-3-540-85989-5},
pages = {70--78},
location = {New York, New York},
doi = {http://dx.doi.org/10.1007/978-3-540-85990-1_9},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
theme = {misc},
abstract="We present a general method for the computation of PDF-based
characteristics of the tissue micro-architecture in MR imaging. The
approach relies on the approximation of the MR signal by a series
expansion based on Spherical Harmonics and Laguerre-Gaussian
functions, followed by a simple projection step that is efficiently
done in a finite dimensional space. The resulting algorithm is
generic, flexible and is able to compute a large set of useful
characteristics of the local tissues structure. We illustrate the
effectiveness of this approach by showing results on synthetic and
real MR datasets acquired in a clinical time-frame.",
url={pdf:=https://brunl01.users.greyc.fr/ARTICLES/miccai08.pdf,Slides:=https://brunl01.users.greyc.fr/ARTICLES/poster.pdf}

 }

@inproceedings{elrhabi:hal-01161832,


TITLE = {{Estimation de la pose d'une cam{'e}ra {`a} partir d'un flux vid{'e}o en s'approchant du temps r{'e}el}},
AUTHOR = {El Rhabi, Youssef and Simon, Loic and Brun, Luc},
URL = {https://hal.archives-ouvertes.fr/hal-01161832},
BOOKTITLE = {{Journ{'e}es francophones des jeunes chercheurs en vision par ordinateur}},
ADDRESS = {Amiens, France},
HAL_LOCAL_REFERENCE = {poster},
YEAR = {2015},
MONTH = Jun,
KEYWORDS = {R{'e}alit{'e} augment{'e}e ; SfM ; SLAM ; calcul de pose temps r{'e}el ; recalage 2D/3D},
url = {PDF:=https://hal.archives-ouvertes.fr/hal-01161832/file/Estimation_de_la_pose_d_une_camera_a_partir_d_un_flux_video_en_s_approchant_du_temps_reel.pdf},
HAL_ID = {hal-01161832},
HAL_VERSION = {v1},
theme="misc"

 }

@article{STANOVIC202514,


title = {Graph Neural Networks with maximal independent set-based pooling: Mitigating over-smoothing and over-squashing},
journal = {Pattern Recognition Letters},
volume = {187},
pages = {14-20},
year = {2025},
issn = {0167-8655},
doi = {https://doi.org/10.1016/j.patrec.2024.11.004},
url = {HAL:=https://hal.science/hal-04848262, PRL:=https://www.sciencedirect.com/science/article/pii/S0167865524003106},
author = {Stevan Stanovic and Benoit GaÃ¼zÃ¨re and Luc Brun},
keywords = {Graph Neural Networks, Graph pooling, Over-squashing, Over-smoothing, Maximal independent sets},
abstract = {Graph Neural Networks (GNNs) have significantly advanced graph-level prediction tasks by utilizing efficient convolution and pooling techniques. However, traditional pooling methods in GNNs often fail to preserve key properties, leading to challenges such as graph disconnection, low decimation ratios, and substantial data loss. In this paper, we introduce three novel pooling methods based on Maximal Independent Sets (MIS) to address these issues. Additionally, we provide a theoretical and empirical study on the impact of these pooling methods on over-smoothing and over-squashing phenomena. Our experimental results not only confirm the effectiveness of using maximal independent sets to define pooling operations but also demonstrate their crucial role in mitigating over-smoothing and over-squashing.},
theme="pattern"

 }

@InProceedings{CI-Wallnig-2024,


author = {Julia Wallnig and Luc Brun and Benoit GaÃ¼zÃ¨re and SÃ©bastien Bougleux and Florian Yger and Blumenthal, David B.},
title = {A Differentiable Approximation of the Graph Edit Distance},
booktitle = {Proceedings of SSPR'2024},
year = 2024,
editor = {Andrea Torsello and Luca Rossi},
series = {LNCS},
month = {September},
address = {Venice, Italy},
organization = {IAPR},
publisher = {Springer},
note = {to be published},
theme="pattern,ged",
abstract="To determine the similarity of labeled graphs, the graph edit
distance (GED) is widely used due to its metric properties on the graph
space and its interpretability. It is defined as the minimal cost of a sequence of edit operations transforming one graph into another one, with
the cost of each edit operation being a parameter of the distance. Although calculating GED is NP-hard, various heuristics exist which, in practice, typically yield tight upper or lower bounds. Since determining appropriate edit operation costs for a given dataset or application can be challenging, it is attractive to learn these costs from the data, e. g., using metric learning architectures. However, for this approach to be feasible, a differentiable algorithm to approximate the GED is required. In this work, we present such an algorithm and show via an empirical evaluation on three datasets that the obtained distances closely match the distances computed by a state-of-the-art combinatorial GED heuristic.",
url={HAL:=https://normandie-univ.hal.science/hal-04740015}

 }

@Article{RI-Seraphim-2024,


author = {Mathieu Seraphim and Alexis Lechervy and Florian Yger and Luc Brun and Olivier Etard},
title = {Automatic Classification of Sleep Stages from EEG Signals Using Riemannian Metrics and Transformer Networks},
journal = {Springer Nature Computer Science},
year = 2024,
month="Oct",
volume="5",
number="7",
pages="953",
theme = "pattern",
abstract="In sleep medicine, assessing the evolution of a subjectâs sleep often involves the costly manual scoring of electroencephalographic (EEG) signals. In recent years, a number of Deep Learning approaches have been proposed
to automate this process, mainly by extracting features from said signals.
However, despite some promising developments in related problems, such as
Brain-Computer Interfaces, analyses of the covariances between brain regions
remain underutilized in sleep stage scoring. Expanding upon our previous work, we investigate the capabilities of SPDTransNet, a Transformer-derived network designed to classify sleep stages from EEG data through timeseries of covariance matrices. Furthermore, we present a novel way of integrating learned signal-wise features into said matrices without sacrificing their Symmetric Definite Positive (SPD) nature. Results: Through comparison with other State-of-the-Art models within a methodology optimized for class-wise performance, we achieve a level of performance at or beyond various State-of-the-Art models, both in single-dataset and - particularly - multi-dataset experiments. In this article, we prove the capabilities of our SPDTransNet model, particularly its adaptability to multi-dataset tasks, within the context of EEG sleep stage scoring - though it could easily be adapted to any classification task involving timeseries of covariance matrices.",
url="SNSharedIt:=https://rdcu.be/dWNI2, HAL:=https://hal.science/hal-04638612v1"

 }

@InProceedings{CI-seraphim-2024,


author = {Mathieu Seraphim and Alexis Lechervy and Florian Yger and Luc Brun and Olivier Etard},
title = {Structure preserving transformers for sequences of SPD matrices},
booktitle = {Proceedings of EUSIPCO 2024},
year = 2024,
pages = {1451-1455},
month = {August},
address = {Lyon, France},
organization = {EURASIP},
url = "Eurasip:=https://eurasip.org/Proceedings/Eusipco/Eusipco2024/pdfs/0001451.pdf, HAL:=https://hal.science/hal-04638595",
theme = "pattern",
abstract ="In recent years, Transformer-based auto-attention
mechanisms have been successfully applied to the analysis of a
variety of context-reliant data types, from texts to images and
beyond, including data from non-Euclidean geometries. In this
paper, we present such a mechanism, designed to classify se-
quences of Symmetric Positive Definite matrices while preserving
their Riemannian geometry throughout the analysis. We apply
our method to automatic sleep staging on timeseries of EEG-
derived covariance matrices from a standard dataset, obtaining
high levels of stage-wise performance."

 }

@inproceedings{CI-StanovicGB23,


author = {Stevan Stanovic and
Benoit Ga{"{u}}z{`{e}}re and
Luc Brun},
editor = {Mario Vento and
Pasquale Foggia and
Donatello Conte and
Vincenzo Carletti},
title = {Maximal Independent Sets for Pooling in Graph Neural Networks},
booktitle = {Graph-Based Representations in Pattern Recognition - 13th {IAPR-TC-15}
International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September
6-8, 2023, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {14121},
pages = {113--124},
publisher = {Springer},
year = {2023},
url = {Springer:=https://link.springer.com/chapter/10.1007/978-3-031-42795-4_11, HAL:=https://hal.science/hal-04160860v1},
doi = {10.1007/978-3-031-42795-4_11},
theme = "pattern",
abstract = "Convolutional Neural Networks (CNNs) have enabled major advances in image classification through convolution and pooling. In particular, image pooling transforms a connected discrete lattice into a reduced lattice with the same connectivity and allows reduction functions to consider all pixels in an image. However, there is no pooling that satisfies these properties for graphs. In fact, traditional graph pooling methods suffer from at least one of the following drawbacks: Graph disconnection or overconnection, low decimation ratio, and deletion of large parts of graphs. In this paper, we present three pooling methods based on the notion of maximal independent sets that avoid these pitfalls. Our experimental results confirm the relevance of maximal independent set constraints for graph pooling. "

 }

@inproceedings{CI-Seraphim23,


author = {Mathieu Seraphim and
Paul Dequidt and
Alexis Lechervy and
Florian Yger and
Luc Brun and
Olivier Etard},
editor = {Nicolas Tsapatsoulis and
Andreas Lanitis and
Marios Pattichis and
Constantinos S. Pattichis and
Christos Kyrkou and
Efthyvoulos Kyriacou and
Zenonas Theodosiou and
Andreas Panayides},
title = {Temporal Sequences of {EEG} Covariance Matrices for Automated Sleep
Stage Scoring with Attention Mechanisms},
booktitle = {Computer Analysis of Images and Patterns - 20th International Conference,
{CAIP} 2023, Limassol, Cyprus, September 25-28, 2023, Proceedings,
Part {II}},
series = {Lecture Notes in Computer Science},
volume = {14185},
pages = {67--76},
publisher = {Springer},
year = {2023},
doi = {10.1007/978-3-031-44240-7_7},
url = {Springer:=https://link.springer.com/chapter/10.1007/978-3-031-44240-7_5, HAL:=https://hal.science/hal-04216925v1},
theme = "pattern",
abstract ="Sleep monitoring has traditionally required expensive equipment and expert assessment. Wearable devices are however becoming a viable option for monitoring sleep. This study investigates methods for autonomously identifying sleep segments base on wearable device data. We employ and evaluate machine and deep learning models on the benchmark MESA dataset, with results showing that they outperform traditional methods in terms of accuracy, F1 score, and Matthews Correlation Coefficient (MCC). The most accurate model, namely Light Gradient Boosting Machine, obtained an F1 score of 0.93 and an MCC of 0.73. Additionally, sleep quality metrics were used to assess the models. Furthermore, it should be noted that the proposed approach is device-agnostic, and more accessible and cost-effective than the traditional polysomnography (PSG) methods."

 }

@InProceedings{CI-paulDequidt2023,


author = "Paul Dequidt and Mathieu Seraphim and Alexis Lechervy and Ivan Igor Gaez and Luc Brun and Olivier Etard",
editor="Juarez, Jose M.
and Marcos, Mar
and Stiglic, Gregor
and Tucker, Allan",
title = "Automatic sleep stage classification on EEG signals using time-frequency representation",
booktitle = "Proceedings of {AIME} 2023, Slovenia",
month = jun,
year = 2023,
publisher = "Springer Nature",
pages="250-259",
theme="pattern",
url ={Springer:=https://link.springer.com/chapter/10.1007/978-3-031-34344-5_30, HAL:=https://hal.science/hal-04249277v1/document},
abstract="Sleep stage scoring based on electroencephalogram (EEG) signals is a repetitive task required for basic and clinical sleep studies. Sleep stages are defined on 30 seconds EEG-epochs from brainwave patterns present in specific frequency bands. Time-frequency representations such as spectrograms can be used as input for deep learning methods. In this paper we compare different spectrograms, encoding multiple EEG channels, as input for a deep network devoted to the recognition of image's visual patterns. We further investigate how contextual input enhance the classification by using EEG-epoch sequences of increasing lengths. We also propose a common evaluation framework to allow a fair comparison between state-of-art methods. Evaluations performed on a standard dataset using this unified protocol show that our method outperforms four state-of-art methods."

 }

@inProceedings{CN-mathieu2023,


author = "Mathieu Seraphim and Paul Dequidt and Alexis Lechervy and Florian Yger and Luc Brun and Olivier Etard",
title = "Analyse automatique de l'Ã©tat de sommeil sur donnÃ©es EEG par utilisation de Transformers et de matrices de covariance",
booktitle = "Proceedings of {ORASIS} 2023, Carqueiranne",
month = may,
year = 2023,
publisher = "AFRIF",
note = "To be published",
theme="pattern",
abstract="Les donnÃ©es Ã©lectroencÃ©phalographiques (EEG) sont communÃ©ment utilisÃ©es en mÃ©decine du sommeil. Il s'agit d'un ensemble de signaux Ã©lectriques cÃ©rÃ©braux issus de diffÃ©rents capteurs, subdivisÃ©s en segments devant Ãªtre annotÃ©s manuellement pour quantifier les diffÃ©rents stades de sommeil. Ces derniÃ¨res annÃ©es, une littÃ©rature croissante s'est accumulÃ©e sur l'automatisation de ce processus d'annotation, offrant des rÃ©sultats prometteurs, mais insuffisants pour une utilisation en milieu clinique.
Nous proposons d'explorer une approche alternative afin d'amÃ©liorer la classification, basÃ©e sur l'Ã©tude de l'information portÃ©e par les covariations entre plusieurs signaux EEG reprÃ©sentatifs de diffÃ©rentes rÃ©gions cÃ©rÃ©brales. Ces covariations prennent la forme de sÃ©quences temporelles de matrices de covariance, exploitÃ©es au travers de mÃ©canismes d'attention Ã  l'Ã©chelle intra-Ã©poque et inter-Ã©poque. Nous validons nos rÃ©sultats sur un jeu de donnÃ©es standard de l'Ãtat de l'Art. ENGLISH: Electroencephalographic data (EEG) is commonly used in sleep medecine. It consists of a number of cerebral electrical signals measured from various brain locations, subdivided into segments that must be manually scored to reflect their sleep stage. These past few years, multiple implementations of an automatization of this scoring process have been attempted, with promising results, although they are not yet accurate enough to see clinical use.
We propose a novel approach, that relies on the information contained within the covariations between multiple EEG signals, each signal reresentative of a different cerebral region. This is done through temporal sequences of covariance matrices, analyzed through attention mechanisms at both the intra- and inter-epoch levels. Evaluation is performed on a standard dataset, for comparison with the State of the Art.",
url="HAL(pdf):=https://hal.science/hal-04055874v2/document, HAL:=https://hal.science/hal-04055874v2"

 }

@InProceedings{CI-Brun2022,


author = {Luc Brun and Benoit Gauzere and Guillaume Renton and Sebastien Bougleux and Florian Yger},
title = {A differentiable approximation for the Linear Sum Assignment Problem with Edition (LSAPE)},
booktitle = {Proceedinds of 26th ICPR 2022},
year = 2022,
month = {August},
address = {MontrÃ©al},
organization = {IAPR},
publisher = {IEEE},
theme="pattern",
url={HAL:=https://hal.archives-ouvertes.fr/hal-03768664, TR(pdf):=https://hal.archives-ouvertes.fr/hal-03454896/file/main.pdf}
abstract="Linear Sum Assignment Problem (LSAP) consists in
mapping two sets of points of equal sizes according to a matrix
encoding the cost of mapping each pair of points. The Linear
Sum Assignment Problem with Edition (LSAPE) extends this
problem by allowing the mapping of sets of different sizes and
adding the possibility to reject some matchings. This problem
is set up by a rectangular cost matrix whose last column and
last line encode the costs of rejecting the match of an element
of respectively the first and the second sets. LSAPE has been
the workhorse of many fundamental graph problems such as
graph edit distance, median graph computation or sub graph
matching. LSAP may be solved using the Hungarian algorithm
while an equivalent efficient discrete algorithm has been designed
for LSAPE. However, while the Sinkhorn algorithm constitutes
a continuous solver for LSAP, no such algorithm yet exists for
LSAPE. This lack of solvers forbids the integration of LSAPE in
Neural networks requiring continuous operations from the input
to the final loss. This paper aims at providing such a solver,
hence paving the way to an integration of LSAPE solvers in
Neural Networks."

 }

@inproceedings{CN-Stanovic2022,


TITLE = {{Ensemble de sommets ind{'e}pendant maximal appliqu{'e} au pooling sur graphes}},
AUTHOR = {Stanovic, Stevan and Ga{"u}z{`e}re, Benoit and Brun, Luc},
URL = {HAL:=https://hal.archives-ouvertes.fr/hal-03696263, Pdf:=https://hal.archives-ouvertes.fr/hal-03696263/file/Ensemble_de_sommets_ind_pendant_maximal_appliqu__au_pooling_sur_graphes.pdf},
BOOKTITLE = {{Congr{`e}s Reconnaissance des Formes, Image, Apprentissage et Perception ( RFIAP)}},
ADDRESS = {VANNES, France},
YEAR = {2022},
MONTH = Jul,
KEYWORDS = {Graph Neural Networks ; Graph Pooling ; Graph Classification ; Maximal Independant Vertex Set ; R{'e}seaux de neurones sur graphes ; Ensemble de sommets ind{'e}pendant maximal ; Classification de graphes ; Pooling sur graphes},
theme="pattern",
abstract={Les rÃ©seaux de neurones convolutifs (CNN) ont permis des avancÃ©es majeures dans la classification d'images grÃ¢ce Ã  la convolution et au pooling. En particulier, le pooling sur image transforme une grille discrÃ¨te connexe en une grille rÃ©duite de mÃªme connexitÃ© et permet aux fonctions de rÃ©duction de prendre en compte tous les pixels de l'image. Cependant, un pooling satisfaisant de telles propriÃ©tÃ©s n'existe pas pour les graphes. En effet, certaines mÃ©thodes sont restreintes Ã  la sÃ©lection de sommets selon leur importance. Ceci induit la crÃ©ation de graphes rÃ©duits non connexes et une perte d'information importante. D'autres mÃ©thodes apprennent un partitionnement flou des sommets causant une hyper-connectivitÃ© du graphe rÃ©duit. Dans cette publication, nous proposons de pallier ces problÃ©matiques Ã  l'aide de notre mÃ©thode de pooling, nommÃ©e MIVSPool. Elle est basÃ©e sur une sÃ©lection de sommets appelÃ©s sommets survivants Ã  l'aide d'un ensemble de sommets indÃ©pendant maximal (MIVS) et d'une affectation des autres sommets aux survivants. Par consÃ©quent, notre mÃ©thode donne la garantie de prÃ©server la totalitÃ© de l'information du graphe lors de sa rÃ©duction. Les rÃ©sultats expÃ©rimentaux montrent une augmentation de l'exactitude de la classification sur plusieurs jeux de donnÃ©es standards.}

 }

@techreport{brun:hal-03454896,


TITLE = {{A new Sinkhorn algorithm with Deletion and Insertion operations}},
AUTHOR = {Brun, Luc and Ga{"u}z{`e}re, Benoit and Bougleux, S{'e}bastien and Yger, Florian},
TYPE = {Research Report},
INSTITUTION = {{GREYC, UMR 6072}},
YEAR = {2021},
MONTH = Nov,
KEYWORDS = {Sinkhorn algorithm ; Linear Sum Assignment problem},
url = {Pdf(HAL):=https://hal.archives-ouvertes.fr/hal-03454896/file/main.pdf,HAL:=https://hal.archives-ouvertes.fr/hal-03454896, ArXiv:=https://arxiv.org/abs/2111.14565, Pdf(ArXiv):=https://arxiv.org/pdf/2111.14565},
HAL_ID = {hal-03454896},
HAL_VERSION = {v1},
theme="pattern",
abstract="This report is devoted to the continuous estimation of an epsilon-assignment. Roughly speaking, an epsilon assignment between two sets V1 and V2 may be understood as a bijective mapping between a sub part of V1 and a sub part of V2 . The remaining elements of V1 (not included in this mapping) are mapped onto an epsilon pseudo element of V2 . We say that such elements are deleted. Conversely, the remaining elements of V2 correspond to the image of the epsilon pseudo element of V1. We say that these elements are inserted. Our algorithms are iterative and differentiable and may thus be easily inserted within a backpropagation based learning framework such as artificial neural networks."

 }

@InProceedings{CI-benNaceur-2021,


author = {Ben Naceur, Mostefa and Luc Brun and Olivier Lezoray},
title = {Lightweight Deep Symmetric Positive Definite Manifold Network for Real-Time 3D Hand Gesture Recognition},
booktitle = {Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition 2021},
year = 2021,
month = {December},
address = {Jodhpur, India},
organization = {IEEE},
theme="pattern",
url= {HAL:=https://hal.science/hal-03531927]},
abstract="This paper proposes a new neural network based on Symmetric Positive Definite (SPD) manifold learning for real-time skeleton-based hand gesture recognition. The transformation of the input skeletal data into SPD matrices allows to encode efficiently high-order statistics such as covariances or correlations between the jointsâ features. These matrices are combined and transformed by our deep neural network which is thus constrained to work on the manifold of such matrices. The online recognition is performed using two sliding windows moving along the gestureâs stream in order to simultaneously detect and classify the occurrence of a new gesture within the stream. The proposed network is validated on a challenging dataset and shows state-of-the-art performances both in terms of accuracy and inference time."

 }

@article{BLUMENTHAL2021101766,


title = {Scalable generalized median graph estimation and its manifold use in bioinformatics, clustering, classification, and indexing},
journal = {Information Systems},
volume = 100,
pages = {101766},
year = {2021},
issn = {0306-4379},
doi = {https://doi.org/10.1016/j.is.2021.101766},
url = {ScienceDirect:=https://www.sciencedirect.com/science/article/pii/S0306437921000284, Code:=https://forge.greyc.fr/projects/gedlibpy/repository},
author = {David B. Blumenthal and Nicolas Boria and SÃ©bastien Bougleux and Luc Brun and Johann Gamper and Benoit GaÃ¼zÃ¨re},
keywords = {Generalized median graphs, Graph edit distance, Graph similarity search, Clustering, Classification, Indexing},
abstract = {In this paper, we present GMG-BCU âa local search algorithm based on block coordinate update for estimating a generalized median graph for a given collection of labeled or unlabeled input graphs. Unlike all competitors, GMG-BCU is designed for both discrete and continuous label spaces and can be configured to run in linear time w.r.t. the size of the graph collection whenever median node and edge labels are computable in linear time. These properties make GMG-BCU usable for applications such as differential microbiome data analysis, graph classification, clustering, and indexing. We also prove theoretical properties of generalized median graphs, namely, that they exist under reasonable assumptions which are met in almost all application scenarios, that they are in general non-unique, that they are NP-hard to compute and APX-hard to approximate, and that no polynomial Î±-approximation exists for any Î± unless the graph isomorphism problem is in P. Extensive experiments on six different datasets show that our heuristic GMG-BCU always outperforms the state of the art in terms of runtime or quality (on most datasets, both w.r.t. runtime and quality), that it is the only available heuristic which can cope with collections containing several thousands of graphs, and that it shows very promising potential when used for the aforementioned applications. GMG-BCU is freely available on GitHub: https://github.com/dbblumenthal/gedlib/.},
theme="pattern"

 }

@inproceedings{CI-GhezaielBL20,


author = {Wajdi Ghezaiel and
Luc Brun and
Olivier L{'{e}}zoray},
title = {Hybrid Network For End-To-End Text-Independent Speaker Identification},
booktitle = {25th International Conference on Pattern Recognition, {ICPR} 2020,
Virtual Event / Milan, Italy, January 10-15, 2021},
pages = {2352--2359},
publisher = {{IEEE}},
year = {2020},
url = {IEEXplore:=https://doi.org/10.1109/ICPR48806.2021.9413293, Slides:=https://brunl01.users.greyc.fr/ARTICLES/Presentation_Ghezaiel_ICPR2020.pdf, PDF:=https://brunl01.users.greyc.fr/ARTICLES/Ghezaiel_icpr2020.pdf,HAL:=https://hal.archives-ouvertes.fr/hal-03086433v1},
timestamp = {Fri, 07 May 2021 12:53:57 +0200},
abstract = "Deep learning has recently improved the performance of Speaker Identification (SI) systems. Promising results have been obtained with Convolutional Neural Networks (CNNs). This success is mostly driven by the advent of large datasets. However in the context of decentralized commercial applications, collection of large amount of training data is not always possible. In addition, robustness of a SI system is adversely effected by short utterances. Therefore, in this paper, we propose a novel text-independent speaker identification system able to identify speakers by learning from only few training short utterances examples. To achieve this, we combine a two-layer wavelet scattering network coupled with a CNN. The proposed architecture takes variable length speech segments. To evaluate the effectiveness of the proposed approach, Timit and Librispeech datasets are used in the experiments. Our experiments shows that our hybrid architecture provides satisfactory results under the constraints of short and limited number of utterances. These experiments also show that our hybrid architecture are competitive with the state of the art.",
theme = "pattern"

 }

@inproceedings{CI-GhezaielBL20b,


author = {Wajdi Ghezaiel and
Luc Brun and
Olivier L{'{e}}zoray},
title = {Wavelet Scattering Transform and {CNN} for Closed Set Speaker Identification},
booktitle = {22nd {IEEE} International Workshop on Multimedia Signal Processing,
{MMSP} 2020, Tampere, Finland, September 21-24, 2020},
pages = {1--6},
publisher = {{IEEE}},
year = {2020},
url = {IEEXplore:=https://doi.org/10.1109/MMSP48831.2020.9287061,PDF:=https://brunl01.users.greyc.fr/ARTICLES/Ghezaiel_MMSP2020.pdf,HAL:=https://hal.archives-ouvertes.fr/hal-02955532v1},
timestamp = {Wed, 13 Jan 2021 17:58:38 +0100},
biburl = {https://dblp.org/rec/conf/mmsp/GhezaielBL20.bib},
abstract = "In real world applications, the performances of speaker identification systems degrade due to the reduction of both the amount and the quality of speech utterance. For that particular purpose, we propose a speaker identification system where short utterances with few training examples are used for person identification. Therefore, only a very small amount of data involving a sentence of 2-4 seconds is used. To achieve this, we propose a novel raw waveform end-to-end convolutional neural network (CNN) for text-independent speaker identification. We use wavelet scattering transform as a fixed initialization of the first layers of a CNN network, and learn the remaining layers in a supervised manner. The conducted experiments show that our hybrid architecture combining wavelet scattering transform and CNN can successfully perform efficient feature extraction for a speaker identification, even with a small number of short duration training samples.",
theme = "pattern"

 }

@inproceedings{ghezaiel:hal-02552042,


TITLE = {{Scattering transform et r{'e}seaux convolutionels pour l'identification du locuteur}},
AUTHOR = {Ghezaiel, Wajdi and Brun, Luc and L{'e}zoray, Olivier and Mokhtari, Myriam},
URL = {HAL:=https://hal.archives-ouvertes.fr/hal-02552042, PDF:=https://hal.archives-ouvertes.fr/hal-02552042/file/RFIAP_2020_paper_20.pdf},
BOOKTITLE = {{RFIAP (Reconnaissance des Formes, Image, Apprentissage et Perception)}},
ADDRESS = {Vannes, France},
YEAR = {2020},
MONTH = Jun,
HAL_ID = {hal-02552042},
HAL_VERSION = {v1},
abstract="Les assistants vocaux sont devenus trÃ¨s populaires ces der-niÃ¨res annÃ©es. Les utilisateurs peuvent contrÃ´ler ces ap-pareils intelligents par la voix et obtenir divers services. CombinÃ©s Ã  la biomÃ©trie, ces dispositifs peuvent permettre de distinguer des profils utilisateurs et sÃ©curiser l'usage de l'appareil. Dans ce scÃ©nario, quelques segments de dis-cours de courte durÃ©e (2-4 sec.) sont utilisÃ©s pour l'au-thentification. Afin de limiter le nombre de paramÃ¨tres utili-sÃ©s pour l'apprentissage, nous proposons de combiner une Wavelet Scattering Transform (ST) et un rÃ©seau convolutif (CNN). Nos expÃ©rimentations montrent que la combinaison ST/CNN extrait efficacement les caractÃ©ristiques de l'iden-titÃ© du locuteur sur des discours de courte durÃ©e. Mots Clef Assistant vocal, identification du locuteur, rÃ©seau de neurones convolutifs, rÃ©seau hybride.",
theme="pattern"

 }

@article{blumenthal-2021,


author = {David B. Blumenthal and
S{'{e}}bastien Bougleux and
Johann Gamper and
Luc Brun},
title = {Upper Bounding {GED} via Transformations to {LSAPE} Based on Rings
and Machine Learning},
journal = {Int. Journal Pattern Recognition and Artificial Intelligence},
volume = {35},
number = {8},
year = {2021},
url = {ArXiv:=http://arxiv.org/abs/1907.00203, DOI:=https://doi.org/10.1142/S0218001421510083},
eprint = {1907.00203},
timestamp = {Sat, 23 Jan 2021 01:12:27 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-1907-00203.bib},
bibsource = {dblp computer science bibliography, https://dblp.org},
theme="pattern",
abstract="The graph edit distance (GED) is a flexible distance measure which is widely used for inexact graph matching. Since its exact computation is NP-hard, heuristics are used in practice. A popular approach is to obtain upper bounds for GED via transformations to the linear sum assignment problem with error-correction (LSAPE). Typically, local structures and distances between them are employed for carrying out this transformation, but recently also machine learning techniques have been used. In this paper, we formally define a unifying framework LSAPE-GED for transformations from GED to LSAPE. We also introduce rings, a new kind of local structures designed for graphs where most information resides in the topology rather than in the node labels. Furthermore, we propose two new ring based heuristics RING and RING-ML, which instantiate LSAPE-GED using the traditional and the machine learning based approach for transforming GED to LSAPE, respectively. Extensive experiments show that using rings for upper bounding GED significantly improves the state of the art on datasets where most information resides in the graphs' topologies. This closes the gap between fast but rather inaccurate LSAPE based heuristics and more accurate but significantly slower GED algorithms based on local search. "


 }

@inproceedings{nguyen-2021,


TITLE = {{Learning Recurrent High-order Statistics for Skeleton-based Hand Gesture Recognition}},
AUTHOR = {Nguyen, Xuan Son and Brun, Luc and L{'e}zoray, Olivier and Bougleux, S{'e}bastien},
BOOKTITLE = {{International Conference on Pattern Recognition (ICPR - IEEE)}},
ADDRESS = {Milan (virtual), Italy},
YEAR = {2021},
url = {HAL:= https://hal.archives-ouvertes.fr/hal-03107675, pdf:=https://hal.archives-ouvertes.fr/hal-03107675/file/ICPR20__home_papercept_iapr.papercept.net_www_conferences_conferences_ICPR20_submissions_0443_FI.pdf},
HAL_ID = {hal-03107675},
HAL_VERSION = {v1},
theme="pattern",
abstract="High-order statistics have been proven useful in the framework of Convolutional Neural Networks (CNN) for a variety of computer vision tasks. In this paper, we propose to exploit high-order statistics in the framework of Recurrent Neural Networks (RNN) for skeleton-based hand gesture recognition. Our method is based on the Statistical Recurrent Units (SRU), an un-gated architecture that has been introduced as an alternative model for Long-Short Term Memory (LSTM) and Gate Recurrent Unit (GRU). The SRU captures sequential information by generating recurrent statistics that depend on a context of previously seen data and by computing moving averages at different scales. The integration of high-order statistics in the SRU significantly improves the performance of the original one, resulting in a model that is competitive to state-of-the-art methods on the Dynamic Hand Gesture (DHG) dataset, and outperforms them on the First-Person Hand Action (FPHA) dataset. "

 }

@article{RI-BORIA2019,

title = "Improved local search for graph edit distance",
journal = "Pattern Recognition Letters",
year = "2020",
volume=129,
pages={19-25},
issn = "0167-8655",
doi = "https://doi.org/10.1016/j.patrec.2019.10.028",
url = "ScienceDirect:=http://www.sciencedirect.com/science/article/pii/S016786551930306X, DraftVersion:=https://arxiv.org/pdf/1907.02929.pdf",
author = "Nicolas Boria and David B. Blumenthal and SÃ©bastien Bougleux and Luc Brun",
keywords = "Graph Edit Distance, local search, stochastic warm start",
abstract = "The graph edit distance (GED) measures the dissimilarity between two graphs as the minimal cost of a sequence of elementary operations transforming one graph into another. This measure is fundamental in many areas such as structural pattern recognition or classification. However, exactly computing GED is NP-hard. Among different classes of heuristic algorithms that were proposed to compute approximate solutions, local search based algorithms provide the tightest upper bounds for GED. In this paper, we present K-REFINE and RANDPOST. K-REFINE generalizes and improves an existing local search algorithm and performs particularly well on small graphs. RANDPOST is a general warm start framework that stochastically generates promising initial solutions to be used by any local search based GED algorithm. It is particularly efficient on large graphs. An extensive empirical evaluation demonstrates that both K-REFINE and RANDPOST perform excellently in practice.",
theme="pattern,ged"

}

@InProceedings{CI-Nguyen2019,


author = {Nguyen, Xuan Son and Brun, Luc and Lezoray, Olivier and Bougleux, Sebastien},
title = {A Neural Network Based on SPD Manifold Learning for Skeleton-Based Hand Gesture Recognition},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019},
theme="pattern",
abstract="This paper proposes a new neural network based on SPD manifold learning for skeleton-based hand gesture recognition. Given the stream of hand's joint positions, our approach combines two aggregation processes on respectively spatial and temporal domains. The pipeline of our network architecture consists in three main stages. The first stage is based on a convolutional layer to increase the discriminative power of learned features. The second stage relies on different architectures for spatial and temporal Gaussian aggregation of joint features. The third stage learns a final SPD matrix from skeletal data. A new type of layer is proposed for the third stage, based on a variant of stochastic gradient descent on Stiefel manifolds. The proposed network is validated on two challenging datasets and shows state-of-the-art accuracies on both datasets."
url="openAccess:=http://openaccess.thecvf.com/content_CVPR_2019/papers/Nguyen_A_Neural_Network_Based_on_SPD_Manifold_Learning_for_Skeleton-Based_CVPR_2019_paper.pdf, HAL:=https://hal.archives-ouvertes.fr/hal-02456437v1, PDF(HAL):=https://hal-normandie-univ.archives-ouvertes.fr/hal-02456437/document, arXiv:=https://arxiv.org/abs/1904.12970"

 }

@article{RI-GRENIER2017,


title = "Chemoinformatics and stereoisomerism: A stereo graph kernel together with three new extensions",
journal = "Pattern Recognition Letters",
volume = "87",
pages = "222 - 230",
year = "2017",
note = "Advances in Graph-based Pattern Recognition",
issn = "0167-8655",
doi = "https://doi.org/10.1016/j.patrec.2016.06.025",
url = "ScienceDirect:=http://www.sciencedirect.com/science/article/pii/S0167865516301581",
author = "Pierre-Anthony Grenier and Luc Brun and Didier Villemin",
keywords = "Chemoinformatics, Stereoisomerism, Graph kernel",
abstract = "In chemoinformatics, Quantitative Structure Activity and Property Relationships (QSAR and QSPR) are two fields which aim to predict properties of molecules thanks to computational techniques. In these fields, graph kernels provide a powerful tool which allows to combine the natural encoding of molecules by graphs with usual statistical tools. However, some molecules may have a same graph but differ by the three dimensional orientation of their atoms in space. These molecules, called stereoisomers, may have different properties which cannot be correctly predicted using usual graph encodings. In a previous study we proposed to encode the stereoisomerism property of each atom by a local subgraph, called minimal stereo subgraph, and we designed a kernel based on the comparison of bags of such subgraphs. This kernel allows to predict properties induced by the stereoisomerism which cannot be correctly predicted using usual graph kernels. However, it has two major drawbacks : it considers each minimal stereo subgraph without taking into account its surroundings, and it considers that two non identical minimal stereo subgraphs have a null similarity. In this paper we present three extensions to tackle those drawbacks. The first extension allows to take into account interactions between minimal stereo subgraphs. The second extension allows to compare the neighborhood of minimal stereo subgraphs. And finally, the third extension provides a measure of similarity between different minimal stereo subgraphs.",
theme="pattern,chemo"

 }

@Article{RI-Blumenthal2019,


author="Blumenthal, David B.
and Boria, Nicolas
and Gamper, Johann
and Bougleux, S{'e}bastien
and Brun, Luc",
title="Comparing heuristics for graph edit distance computation",
journal="The VLDB Journal",
year="2020",
volume=29,
pages="419-458",
month="Jul",
day="15",
abstract="Because of its flexibility, intuitiveness, and expressivity, the graph edit distance (GED) is one of the most widely used distance measures for labeled graphs. Since exactly computing GED is NP-hard, over the past years, various heuristics have been proposed. They use techniques such as transformations to the linear sum assignment problem with error correction, local search, and linear programming to approximate GED via upper or lower bounds. In this paper, we provide a systematic overview of the most important heuristics. Moreover, we empirically evaluate all compared heuristics within an integrated implementation.",
issn="0949-877X",
doi="10.1007/s00778-019-00544-1",
url="Springer:=https://doi.org/10.1007/s00778-019-00544-1, HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-02189832",
theme={pattern,ged}

 }

@InProceedings{CI-Blumenthal-2019,


author = {David Blumenthal and SÃ©bastien Bougleux and Johann Gamper and Luc Brun},
title = {GEDLIB: A C++ Library for Graph Edit Distance Computation},
booktitle = {12th IAPR TC15 Workshop on Graph-Based Representation in Pattern Recognition (GbR)},
year = 2019,
editor = {Donatello Conte and Jean-Yves Ramel and Pasquale Foggia},
volume = 11510,
series = {LNCS},
pages = {14-24},
month = {June},
address = {Tours},
organization = {IAPR TC15},
publisher = {Springer},
url={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-02162839, Python Binding(GIT):=https://forge.greyc.fr/projects/gedlibpy/repository},
theme={pattern,ged},
abstract={The graph edit distance (GED) is a flexible graph dissimilarity measure widely used within the structural pattern recognition field. In this paper, we present GEDLIB, a C++ library for exactly or approximately computing GED. Many existing algorithms for GED are already implemented in GEDLIB. Moreover, GEDLIB is designed to be easily extensible: for implementing new edit cost functions and GED algorithms, it suffices to implement abstract classes contained in the library. For implementing these extensions, the user has access to a wide range of utilities, such as deep neural networks, support vector machines, mixed integer linear programming solvers, a blackbox optimizer, and solvers for the linear sum assignment problem with and without error-correction}

 }

@inproceedings{CI-brun2018,


TITLE = {{A structural approach to Person Re-identification problem}},
AUTHOR = {Brun, Luc and Mahboubi, Amal and Conte, Donatelo},
BOOKTITLE = {{24th International Conference on Pattern Recognition (ICPR)}},
ADDRESS = {P{'e}kin, China},
YEAR = {2018},
pages={1616-1621},
MONTH = Aug,
url = {HAL:= https://hal-normandie-univ.archives-ouvertes.fr/hal-01865218,HAL(PDF):=https://hal-normandie-univ.archives-ouvertes.fr/hal-01865218/document},
note={ISBN: 978-1-5386-3787-6},
theme={pattern,ged},
abstract={Although it has been studied extensively during past decades, object tracking is still a difficult problem due to many challenges. Several improvements have been done, but more and more complex scenes (dense crowd, complex interactions) need more sophisticated approaches. Particularly long-term tracking is an interesting problem that allow to track objects even after it may become longtime occluded or it leave/re-enter the field-of-view. In this case the major challenges are significantly changes in appearance, scale and so on. At the heart of the solution of long-term tracking is the re-identification technique, that allows to identify an object coming back visible after an occlusion or re-entering on the scene. This paper proposes an approach for pedestrian re-identification based on structural representation of people. The experimental evaluation is carried out on two public data sets (ETHZ and CAVIAR4REID datasets) and they show promising results compared to others state-of-the-art approaches.}

 }

@InProceedings{CI-boria-2019,


author = {Nicolas Boria and SÃ©bastien Bougleux and Benoit GaÃ¼zÃ¨re and Luc Brun},
title = {Generalized Median Graph via Iterative Alternate Minimizations},
booktitle = {Proceedings of the International 12th workshop on Graph-Based Representation in Pattern Recognition},
year = 2019,
editor = {Donatello Conte and Jean-Yves Ramel},
series = {LNCS},
month = {June},
address = {Tours},
organization = {IAPR},
publisher = {Springer},
url={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-02162838},
theme="pattern",
abstract="Computing a graph prototype may constitute a core element
for clustering or classification tasks. However, its computation is an NP-
Hard problem, even for simple classes of graphs. In this paper, we propose
an efficient approach based on block coordinate descent to compute a
generalized median graph from a set of graphs. This approach relies on a
clear definition of the optimization process and handles labeling on both
edges and nodes. This iterative process optimizes the edit operations to
perform on a graph alternatively on nodes and edges. Several experiments
on different datasets show the efficiency of our approach."

 }

@InProceedings{CI-Son-2019,


author = {Nguyen, Xuan Son and Luc Brun and Olivier Lezoray and SÃ©bastien Bougleux},
title = {Skeleton-Based Hand Gesture Recognition by Learning SPD Matrices with Neural Networks},
booktitle = {Proceedings of the 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2019)},
year = 2019,
organization = {IEEE},
theme="pattern",
url={HAL:= https://hal.archives-ouvertes.fr/hal-02133684},
abstract=" In this paper, we propose a new hand gesture recognition
method based on skeletal data by learning SPD
matrices with neural networks. We model the hand
skeleton as a graph and introduce a neural network
for SPD matrix learning, taking as input the 3D
coordinates of hand joints. The proposed network is
based on two newly designed layers that transform a
set of SPD matrices into a SPD matrix. For gesture
recognition, we train a linear SVM classifier using
features extracted from our network. Experimental
results on a challenging dataset (Dynamic Hand
Gesture dataset from the SHREC 2017 3D Shape
Retrieval Contest) show that the proposed method
outperforms state-of-the-art methods"

 }

@InProceedings{CI-blumenthal18-2,


author = {David Blumenthal and SÃ©bastien Bougleux and Johann Gamper and Luc Brun},
title = {Quasimetric Graph Edit Distance As a Compact Quadratic Assignment Problem},
booktitle = {Proceedings of ICPR 2018},
year = 2018,
pages = {934-939},
month = {August},
address = {Beijing, China},
organization = {IAPR},
publisher = {IEEE},
note={ISBN: ISBN: 978-1-5386-3787-6},
theme={pattern,ged},
url={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01865214, HAL(PDF):= https://hal-normandie-univ.archives-ouvertes.fr/hal-01865214/document},
abstract={The graph edit distance (GED) is a widely used distance measure for attributed graphs. It has recently been shown that the problem of computing GED, which is a NP-hard optimization problem, can be formulated as a quadratic assignment problem (QAP). This formulation is useful, since it allows to derive well performing approximative heuristics for GED from existing techniques for QAP. In this paper, we focus on the case where the edit costs that underlie GED are quasimetric. This is the case in many applications of GED. We show that, for quasimetric edit costs, it is possible to reduce the size of the corresponding QAP formulation. An empirical evaluation shows that this reduction significantly speeds up the QAP-based approximative heuristics for GED. }

 }

@InProceedings{CI-blumenthal18,


author = {David Blumenthal and SÃ©bastien Bougleux and Johann Gamper and Luc Brun},
title = {Ring Based Approximation of Graph Edit Distance},
booktitle = {Proceedins of Structural, Syntactic, and Statistical Pattern Recognition (SSPR)'2018},
year = 2018,
pages= {293-303},
month = {August},
address = {Beijing},
organization = {IAPR},
editor="Bai, Xiao
and Hancock, Edwin R.
and Ho, Tin Kam
and Wilson, Richard C.
and Biggio, Battista
and Robles-Kelly, Antonio",
publisher = {Springer International Publishing},
isbn="978-3-319-97785-0",
theme={pattern,ged},
url={PDF(local):=https://brunl01.users.greyc.fr/ARTICLES/sspr18ring-bged.pdf, HAL(PDF):=https://hal-normandie-univ.archives-ouvertes.fr/hal-01865194/file/sspr18ring-bged.pdf, HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01865194},
abstract={The graph edit distance (GED) is a flexible graph dissimilar-ity measure widely used within the structural pattern recognition field. A widely used paradigm for approximating GED is to define local structures rooted at the nodes of the input graphs and use these structures to transform the problem of computing GED into a linear sum assignment problem with error correction (LSAPE). In the literature, different local structures such as incident edges, walks of fixed length, and induced subgraphs of fixed radius have been proposed. In this paper, we propose to use rings as local structure, which are defined as collections of nodes and edges at fixed distances from the root node. We empirically show that this allows us to quickly compute a tight approximation of GED.}

 }

@InProceedings{CI-Daller2018b,


author = {'Evariste Daller and SÃ©bastien Bougleux and Luc Brun and Olivier L'ezoray},
title = {Local Patterns and Supergraph for Chemical Graph Classification with Convolutional Networks},
booktitle = {Proceedins of Structural, Syntactic, and Statistical Pattern Recognition(SSPR)'2018},
year = 2018,
month = {August},
address = {Beijing},
pages="97--106",
editor="Bai, Xiao
and Hancock, Edwin R.
and Ho, Tin Kam
and Wilson, Richard C.
and Biggio, Battista
and Robles-Kelly, Antonio",
organization = {IAPR},
publisher = {Springer International Publishing},
theme={pattern,ged},
url={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01865180, HAL(PDF):=https://hal-normandie-univ.archives-ouvertes.fr/hal-01865180/file/sspr-2018.pdf},
abstract={Convolutional neural networks (CNN) have deeply impacted the field of machine learning. These networks, designed to process objects with a fixed topology, can readily be applied to images, videos and sounds but cannot be easily extended to structures with an arbitrary topology such as graphs. Examples of applications of machine learning to graphs include the prediction of the properties molecular graphs, or the classification of 3D meshes. Within the chemical graphs framework, we propose a method to extend networks based on a fixed topology to input graphs with an arbitrary topology. We also propose an enriched feature vector attached to each node of a chemical graph and a new layer interfacing graphs with arbitrary topologies with a full connected layer. }

 }

@InProceedings{CN-Daller2018c,


author = {'Evariste Daller and SÃ©bastien Bougleux and Luc Brun and Olivier Lezoray},
title = {Motifs locaux et super-graphe pour la classification de graphes symboliques avec des r'eseaux convolutionnels},
booktitle = {Actes de la con'erence RFIAP 2018},
year = 2018,
month = {Juin},
address = {Marne la val'ee},
organization = {AFRIF},
theme={pattern,ged},
url={HAL:=https://hal.archives-ouvertes.fr/hal-01796587v1},
abstract="Les r'eseaux convolutionnels ont r'evolutionn'e le domaine de l'apprentissage machine. Ces r'eseaux s'appliquent naturellement aux images, vid'eos et aux sons. En revanche, la structure fixe de leur couche d'entr'ee ne permet pas de les 'etendre facilement Ã  des structures de topologie arbitraire tels que les graphes. On peut citer comme exemples d'applications la pr'ediction de propri'et'es de mol'ecules chimiques ou la classification de maillages 3D. Dans le cadre de graphes symboliques, nous proposons une m'ethode permettant d'appliquer des r'eseaux bas'es sur une topologie fixe de la couche d'entr'ee Ã  des graphes de topologie arbitraire. Nous proposons 'egalement d'enrichir l'information contenu dans chaque sommet pour am'eliorer la pr'ediction de ses propri'et'es ainsi qu'une nouvelle couche permettant d'interfacer des graphes de topologie arbitraire avec une couche entiÃ¨rement connect'ee."

 }

@InProceedings{CI-Boria2018,


author = {Nicolas Boria and SÃ©bastien Bougleux and Luc Brun},
title = {Approximating GED using a Stochastic Generator and Multistart IPFP},
booktitle = {Proceedings of SSPR'2018},
year = 2018,
pages= "460--469",
month = {August},
organization = {IAPR},
publisher = {Springer International Publishing},
editor="Bai, Xiao
and Hancock, Edwin R.
and Ho, Tin Kam
and Wilson, Richard C.
and Biggio, Battista
and Robles-Kelly, Antonio",
theme={pattern,ged},
url={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01865351, HAL(PDF):= https://hal-normandie-univ.archives-ouvertes.fr/hal-01865351/document},
abstract={ The Graph Edit Distance defines the minimal cost of a sequence of elementary operations transforming a graph into another graph. This versatile concept with an intuitive interpretation is a fundamental tool in structural pattern recognition. However, the exact computation of the Graph Edit Distance is N P-complete. Iterative algorithms such as the ones based on Franck-Wolfe method provide a good approximation of true edit distance with low execution times. However, underlying cost function to optimize being neither concave nor convex, the accuracy of such algorithms highly depends on the initialization. In this paper, we propose a smart random initializer using promising parts of previously computed solutions.},
isbn="978-3-319-97785-0"

 }

@InProceedings{CI-daller2018,


author = {Evariste Daller and SÃ©bastien Bougleux and Benoit GaÃ¼zÃ¨re and Luc Brun},
title = {Approximate Graph Edit Distance by Several Local Searches in Parallel},
booktitle = {7th Internation Conference on Pattern Recognition Applications and Methods},
year = 2018,
editor = {Ana Fred},
month = "jan",
theme="pattern,ged",
url={HAL:= https://hal.archives-ouvertes.fr/hal-01664529v1},
abstract="Solving or approximating the linear sum assignment problem (LSAP) is an important step of several constructive and local search strategies developed to approximate the graph edit distance (GED) of two attributed graphs, or more generally the solution to quadratic assignment problems. Constructive strategies find a first estimation of the GED by solving an LSAP. This estimation is then refined by a local search strategy. While these search strategies depend strongly on the initial assignment, several solutions to the linear problem usually exist. They are not taken into account to get better estimations. All the estimations of the GED based on an LSAP select randomly one solution. This paper explores the insights provided by the use of several solutions to an LSAP, refined in parallel by a local search strategy based on the relaxation of the search space, and conditional gradient descent. Two other generators of initial assignments are also considered, approximate solutions to an LSAP and random assignments. Experimental evaluations on several datasets show that the proposed estimation is comparable to more global search strategies in a reduced computational time."

 }

@article{RI-ABUAISHEH201796,


title = "Graph edit distance contest: Results and future challenges",
journal = "Pattern Recognition Letters",
volume = "100",
number = "Supplement C",
pages = "96 - 103",
year = "2017",
issn = "0167-8655",
doi = "https://doi.org/10.1016/j.patrec.2017.10.007",
url = "HAL:=https://hal.archives-ouvertes.fr/hal-01624592, ScienceDirect:=http://www.sciencedirect.com/science/article/pii/S0167865517303690",
author = "Zeina Abu-Aisheh and Benoit GaÃ¼zÃ¨re and SÃ©bastien Bougleux and Jean-Yves Ramel and Luc Brun and Romain Raveaux and Pierre H'eroux and SÃ©bastien Adam",
keywords = "Graph edit distance, Pattern Recognition, Binary linear programming, Quadratic assignment, Branch-and-bound",
theme={pattern,ged},
abstract = "Abstract Graph Distance Contest (GDC) was organized in the context of ICPR 2016. Its main challenge was to inspect and report performances and effectiveness of exact and approximate graph edit distance methods by comparison with a ground truth. This paper presents the context of this competition, the metrics and datasets used for evaluation, and the results obtained by the eight submitted methods. Results are analyzed and discussed in terms of computation time and accuracy. We also highlight the future challenges in graph edit distance regarding both future methods and evaluation metrics. The contest was supported by the Technical Committee on Graph-Based Representations in Pattern Recognition (TC-15) of the International Association of Pattern Recognition (IAPR)."

 }

@article{RI-BRUN2018,


title = "Trends in graph-based representations for Pattern Recognition",
journal = "Pattern Recognition Letters",
year = "2018",
issn = "0167-8655",
doi = "https://doi.org/10.1016/j.patrec.2018.03.016",
url = "http://www.sciencedirect.com/science/article/pii/S0167865518300953",
author = "Luc Brun and Pasquale Foggia and Mario Vento",
keywords = "Graph-based representations, Graph matching, Graph edit distance, Graph kernels",
theme={pattern,ged},
abstract = "In this paper we try to examine recent trends on the use of graph-based representations in Pattern Recognition, using as a vantage point the 11th IAPR-TC15 Workshop GbR2017, dedicated to this topic. A survey of the paper presented at GbR2017 will give us the opportunity to reflect on the directions where the interest of the research community working on this subject is moving."

 }

@article{RI-BOUGLEUX2018,


title = "Fast linear sum assignment with error-correction and no cost constraints",
journal = "Pattern Recognition Letters",
volume = "134",
pages = {37-45},
year = "2018",
issn = "0167-8655",
doi = "https://doi.org/10.1016/j.patrec.2018.03.032",
url = "ScienceDirect:=http://www.sciencedirect.com/science/article/pii/S0167865518301120, HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-02110718v1",
author = "SÃ©bastien Bougleux and Benoit GaÃ¼zÃ¨re and David B. Blumenthal and Luc Brun",
keywords = "Inexact graph matching, Linear assignment, Graph edit distance",
theme={pattern,ged},
abstract = "We propose an algorithm that efficiently solves the linear sum assignment problem with error-correction and no cost constraints. This problem is encountered for instance in the approximation of the graph edit distance. The fastest currently available solvers for the linear sum assignment problem require the pairwise costs to respect the triangle inequality. Our algorithm is as fast as these algorithms, but manages to drop the cost constraint. The main technical ingredient of our algorithm is a cost-dependent factorization of the node substitutions."

 }

@inproceedings{CI-Bougleux2017,


TITLE = {{A Hungarian Algorithm for Error-Correcting Graph Matching}},
AUTHOR = {Bougleux, S{'e}bastien and Ga{"u}z{`e}re, Benoit and Brun, Luc},
BOOKTITLE = {{11th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition (GbRPR 2017)}},
ADDRESS = {AnaCapri, Italy},
ORGANIZATION = {{Pasquale Foggia}},
EDITOR = {Pasquale Foggia and Cheng-Lin Liu and Mario Vento},
PUBLISHER = {{Springer}},
SERIES = {Lecture notes in Computer Sciences (LNCS)},
VOLUME = {10310},
PAGES = {118-127},
YEAR = {2017},
MONTH = May,
DOI = {10.1007/978-3-319-58961-9_11},
KEYWORDS = {Graph edit distance ; Bipartite matching ; Error-correcting matching ; Hungarian algorithm},
URL = {PDF(HAL):=https://hal.archives-ouvertes.fr/hal-01540920/file/hungarian-algorithm-error.pdf, www page :=https://hal.archives-ouvertes.fr/hal-01540920},
HAL_ID = {hal-01540920},
HAL_VERSION = {v1},
theme={pattern,ged}

 }

@article{RI-Bougleux2016,

title = "Graph edit distance as a quadratic assignment problem ",
journal = "Pattern Recognition Letters ",
pages = " 38-46",
volume=87,
year = 2017,
note = "Impact factor : 1.586",
issn = "0167-8655",
doi = "http://dx.doi.org/10.1016/j.patrec.2016.10.001",
url = "ScienceDirect:=http://www.sciencedirect.com/science/article/pii/S0167865516302665,HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01613964v1",
author = "SÃ©bastien Bougleux and Luc Brun and Vincenzo Carletti and Pasquale Foggia and Benoit GaÃ¼zÃ¨re and Mario Vento",
keywords = "Structural pattern recognition",
keywords = "Graph edit distance",
keywords = "Edit paths",
keywords = "Quadratic assignment problem",
keywords = "Combinatorial optimization",
keywords = "Relaxation methods ",
abstract = "Abstract The Graph Edit Distance (GED) is a flexible measure of dissimilarity between graphs which arises in error-correcting graph matching. It is defined from an optimal sequence of edit operations (edit path) transforming one graph into another. Unfortunately, the exact computation of this measure is NP-hard. In the last decade, several approaches were proposed to approximate the {GED} in polynomial time, mainly by solving linear programming problems. Among them, the bipartite {GED} received much attention. It is deduced from a linear sum assignment of the nodes of the two graphs, which can be efficiently computed by Hungarian-type algorithms. However, edit operations on nodes and edges are not handled simultaneously, which limits the accuracy of the approximation. To overcome this limitation, we propose to extend the linear assignment model to a quadratic one. This is achieved through the definition of a family of edit paths induced by assignments between nodes. We formally show that the GED, restricted to the paths in this family, is equivalent to a quadratic assignment problem. Since this problem is NP-hard, we propose to compute an approximate solution by adapting two algorithms: Integer Projected Fixed Point method and Graduated Non Convexity and Concavity Procedure. Experiments show that the proposed approach is generally able to reach a more accurate approximation of the exact {GED} than the bipartite GED, with a computational cost that is still affordable for graphs of non trivial sizes. ",
theme={pattern,ged}

}

@InProceedings{Grenier2016,


author = {Grenier, Pierre Anthony and Luc Brun and Didier Villemin},
title = {Taking into Account Stereoisomerism in the Prediction of Molecular Properties},
booktitle = {Proceedings of ICPR 2016},
year = 2016,
month = {December},
address = {Cancun},
organization = {IAPR},
pages ="1543-1548",
publisher = {IEEE},
theme= "pattern,chemo",
url={PDF:=https://brunl01.users.greyc.fr/ARTICLES/grenier2016.pdf, HAL:=https://hal.archives-ouvertes.fr/hal-01418939}

 }

@inproceedings{RhabiSBCL16,


author = {Rhabi, Youssef El and
Lo{"{i}}c Simon and
Luc Brun and
Llados Canet, Josep and
Felipe Lumbreras},
title = {Information Theoretic Rotationwise Robust Binary Descriptor Learning},
booktitle = {Structural, Syntactic, and Statistical Pattern Recognition - Joint
{IAPR} International Workshop, {S+SSPR} 2016, M{'{e}}rida, Mexico,
November 29 - December 2, 2016, Proceedings},
pages = {368--378},
year = {2016},
month ={November},
url = {Springer:=http://dx.doi.org/10.1007/978-3-319-49055-7_33, HAL:=https://hal.archives-ouvertes.fr/hal-01418934},
theme="pattern"

 }

@inproceedings{GauzereBB16,


author = {Benoit Ga{"{u}}z{`{e}}re and
S{'{e}}bastien Bougleux and
Luc Brun},
title = {Approximating Graph Edit Distance Using {GNCCP}},
booktitle = {Structural, Syntactic, and Statistical Pattern Recognition - Joint
{IAPR} International Workshop, {S+SSPR} 2016, M{'{e}}rida, Mexico,
November 29 - December 2, 2016, Proceedings},
pages = {496--506},
year = {2016},
month = {November},
crossref = {DBLP:conf/sspr/2016},
url = {Springer:=http://dx.doi.org/10.1007/978-3-319-49055-7_44, HAL:=https://hal.archives-ouvertes.fr/hal-01418936},
doi = {10.1007/978-3-319-49055-7_44},
theme= "pattern,ged"

 }

@inproceedings{CI-bougleux2016,


TITLE = {{Graph Edit Distance as a Quadratic Program}},
AUTHOR = {Bougleux, S{'e}bastien and Ga{"u}z{`e}re, Benoit and Brun, Luc},
URL = {HAL:=https://hal.archives-ouvertes.fr/hal-01418937, PDF:=https://hal.archives-ouvertes.fr/hal-01418937/file/icpr.pdf},
BOOKTITLE = {{ICPR 2016 23rd International Conference on Pattern Recognition}},
pages ="1701â1706",
ADDRESS = {Cancun, Mexico},
PUBLISHER = {{IEEE}},
SERIES = {Proceedings of ICPR 2016},
YEAR = {2016},
MONTH = December,
KEYWORDS = {Graph edit distance ; IPFP ; },
HAL_ID = {hal-01418937},
HAL_VERSION = {v1},
theme="pattern,ged"

 }

@techreport{bougleux2016,


TITLE = {{Linear Sum Assignment with Edition}},
AUTHOR = {Bougleux, S{'e}bastien and Brun, Luc},
TYPE = {Research Report},
INSTITUTION = {{Normandie Universit{'e} ; GREYC CNRS UMR 6072}},
YEAR = {2016},
MONTH = March,
KEYWORDS = {Bipartite graph matching ; Edit Distance ; Hungarian Method ; Assignment Problem ; Matching Technique ; Assignment algorithms},
url = {HAL:=https://hal.archives-ouvertes.fr/hal-01288288, PDF:= https://hal.archives-ouvertes.fr/hal-01288288/file/lsape-rr.pdf, arXiv:=https://arxiv.org/abs/1603.04380},
HAL_ID = {hal-01288288},
HAL_VERSION = {v3},
theme= "pattern,ged"

 }

@InProceedings{Hafiane2015,


author = {Rachid Hafiane and Luc Brun and Salvatore Tabbone},
title = {Incremental embedding within a dissimilarity-based framework},
booktitle = { Proceedings of the 10 th IAPR-TC15 Workshop on
Graph-based Representations (GbR) in Pattern Recognition},
year = 2015,
editor = {Cheng-Lin Liu and
Bin Luo and
Kropatsch, Walter G. and
Jian Cheng},
volume = 9069,
series = {LNCS},
pages = {64-73},
month = {May},
address = {Bejing, China},
organization = {IAPR TC15},
publisher = {Springer International Publishing},
note = {aceptance rate:67.9% },
theme= "pattern"

 }

@InProceedings{Grenier2015,


author = {Pierre-Anthony Grenier and Luc Brun and Didier Villemin},
title = {From bags to graphs of stereo subgraphs in order to predict molecule's properties},
booktitle = { Proceedings of the 10 th IAPR-TC15 Workshop on
Graph-based Representations (GbR) in Pattern Recognition},
year = 2015,
editor = {Cheng-Lin Liu and
Bin Luo and
Kropatsch, Walter G. and
Jian Cheng},
volume = 9069,
series = {LNCS},
pages = {305-314},
month = {May},
address = {Bejing, China},
organization = {IAPR TC15},
url ={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01848014v1, ResearchGate:=https://www.researchgate.net/publication/300896987_From_Bags_to_Graphs_of_Stereo_Subgraphs_in_Order_to_Predict_Molecule'S_Properties},
publisher = {Springer International Publishing},
note = {aceptance rate:67.9% },
theme= "pattern,chemo",
abstract={Quantitative Structure Activity and Property Relationships (QSAR and QSPR), aim to predict properties of molecules thanks to computational techniques. In these fields, graphs provide a natural encoding of molecules. However some molecules may have a same graph but differ by the three dimensional orientation of their atoms in space. These molecules, called stereoisomers, may have different properties which cannot be correctly predicted using usual graph encodings. In a previous paper we proposed to encode the stereoisomerism property of each atom by a local subgraph. A kernel between bags of such subgraphs then provides a similarity measure incorporating stereoisomerism properties. However, such an approach does not take into account potential interactions between these subgrahs. We thus propose in this paper, a method to take these interactions into account hence providing a global point of view on moleculesâs stereoisomerism properties.}

 }

@InProceedings{Vincenzo2015,


author = {Vincenzo Carletti and Benoit GaÃ¼zÃ¨re and Luc Brun and Mario Vento},
title = {Approximate Graph Edit Distance Computation Combining Bipartite Matching and Exact Neighborhood Substructure Distance},
booktitle = {Proceedings of the 10 th IAPR-TC15 Workshop on
Graph-based Representations (GbR) in Pattern Recognition},
year = 2015,
editor = {Cheng-Lin Liu and
Bin Luo and
Kropatsch, Walter G. and
Jian Cheng},
volume = 9069,
series = {LNCS},
pages = {188-197},
month = {May},
address = {Bejing, China},
organization = {IAPR TC15},
url ={draft version (PDF) :=https://brunl01.users.greyc.fr/ARTICLES/gbr2015Carletti.pdf, HAL:= https://hal.archives-ouvertes.fr/hal-01389626},
publisher = {Springer International Publishing},
note = {aceptance rate:67.9% },
theme= "pattern,ged",
abstract={Graph edit distance corresponds to a flexible graph dissimilarity measure. Unfortunately, its computation requires an exponential complexity according to the number of nodes of both graphs being compared. Some heuristics based on bipartite assignment algorithms have been proposed in order to approximate the graph edit distance. However, these heuristics lack of accuracy since they are based either on small patterns providing a too local information or walks whose tottering induce some bias in the edit distance calculus. In this work, we propose to extend previous heuristics by considering both less local and more accurate patterns defined as subgraphs defined around each node.}

 }

@article{BrunAction2015,


title = {Action recognition by using kernels on aclets sequences},
author = {L. Brun and G. Percannella and A. Saggese and M. Vento},
url = {CVIU:=http://www.sciencedirect.com/science/article/pii/S1077314215001988,HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01921521v1},
year = {2016},
journal = {Computer Vision and Image Understanding},
keywords = {Video analysis and interpretation},
pubstate = {published},
tppubtype = {article},
pages={3-13},
volume=144,
theme="pattern",
abstract= "In this paper we propose a method for human action recognition based on a string kernel framework. An action is represented as a string, where each symbol composing it is associated to an aclet, that is an atomic unit of the action encoding a feature vector extracted from raw data. In this way, measuring similarities between actions leads to design a similarity measure between strings. We propose to define this stringâs similarity using the global alignment kernel framework. In this context, the similarity between two aclets is computed by a novel soft evaluation method based on an enhanced gaussian kernel. The main advantage of the proposed approach lies in its ability to effectively deal with actions of different lengths or different temporal scales as well as with noise introduced during the features extraction step. The proposed method has been tested over three publicly available datasets, namely the MIVIA, the CAD and the MHAD, and the obtained results, compared with several state of the art approaches, confirm the effectiveness and the applicability of our system in real environments, where unexperienced operators can easily configure it."

 }

@techreport{bougleux:hal-01246709,


TITLE = {{A Quadratic Assignment Formulation of the Graph Edit Distance}},
AUTHOR = {Bougleux, S{'e}bastien and Brun, Luc and Carletti, Vincenzo and Foggia, Pasquale and Ga{"u}z{`e}re, Benoit and Vento, Mario},
TYPE = {Research Report},
INSTITUTION = {{Normandie Universit{'e} ; GREYC CNRS UMR 6072 ; LITIS}},
YEAR = {2015},
MONTH = Dec,
KEYWORDS = { Relaxation methods ; Structural pattern recognition ; Graph edit distance ; Edit paths ; Quadratic assignment problem ; Combinatorial optimization},
url = {PDF:= https://hal.archives-ouvertes.fr/hal-01246709/file/technical_report_ged.pdf, HAL:=https://hal.archives-ouvertes.fr/hal-01246709,arXiv:=https://arxiv.org/abs/1512.07494},
HAL_ID = {hal-01246709},
HAL_VERSION = {v1},
theme="pattern,ged"

 }

@inproceedings{CI-visapp15_ed,


title = {Recognition of human actions using edit distance on aclet strings},
author = {L. Brun and P. Foggia and A. Saggese and M. Vento},
year = {2015},
date = {2015-03-13},
url = {HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01921532v1},
booktitle = {V.I.S.A.P.P 2015},
keywords = {Video analysis and interpretation},
theme="pattern"

 }

@inproceedings{CI-avss14_string,


title = {HacK: A System for the Recognition of Human Actions by Kernels of Visual Strings},
author = {L. Brun and G. Percannella and A. Saggese and M. Vento},
editor = {IEEE},
isbn = {978-1-4799-4871-0/14},
year = {2014},
date = {2014-08-29},
booktitle = {IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS 2014)},
address={Seoul, Korea},
url ={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01921540v1},
keywords = {Video analysis and interpretation},
theme="pattern"

 }

@inproceedings{CI-avss14_vrs1,


title = {Detection of Anomalous Driving Behaviors by Unsupervised Learning of Graphs},
author = {L. Brun and B. Cappellania and A. Saggese and M. Vento},
editor = {IEEE},
isbn = {978-1-4799-4871-0/14},
year = {2014},
date = {2014-08-29},
booktitle = {IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS 2014)},
address={Seoul, Korea},
url ={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-01921543v1},
keywords = {Video analysis and interpretation},
theme="pattern"

 }

@inproceedings{CI-avss14_vrs2,


title = {A Reliable String Kernel based Approach for Solving Queries by Sketch},
author = {L. Brun and A. Saggese and M. Vento},
editor = {IEEE},
isbn = {978-1-4799-4871-0/14},
year = {2014},
date = {2014-08-29},
booktitle = {IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS 2014)},
address={Seoul, Korea},
keywords = {Video analysis and interpretation},
theme="pattern",
url = {ResearchGate:=https://www.researchgate.net/publication/265167481_A_Reliable_String_Kernel_based_Approach_for_Solving_Queries_by_Sketch#fullTextFileContent},
abstract ={In this paper we propose a novel and efficient method for solving queries by sketch in traffic scenarios, aiming to find the k nearest neighbor trajectories to the one hand drawn by the human operator. Each trajectory is represented as a sequence of symbols, namely a string, and it is stored into a k-d tree by taking into account the similarity between trajectories, evaluated by a global fast alignment kernel. The experimentation has been conducted over the standard MIT trajectories dataset and results confirm the effective- ness and the robustness of the proposed approach}

 }

@article{CI-Saggesse-elcvia_14,


title = {Detecting and indexing moving objects for Behavior Analysis by Video and Audio Interpretation},
author = {A. Saggese and L. Brun and M. Vento},
url = {http://elcvia.cvc.uab.es/article/view/603},
issn = {1577-5097},
year = {2014},
date = {2014-06-07},
journal = {Electronic Letters on Computer Vision and Image Analysis},
volume = {13},
number = {2},
keywords = {Audio analysis and interpretation, Video analysis and interpretation},
theme="pattern"

 }

@inproceedings{CI-Gauzere2014b,


url = {HAL:= http://hal.archives-ouvertes.fr/hal-01066389, Pdf:=http://hal.archives-ouvertes.fr/hal-01066389/PDF/GauzereAl-ICPR2014-Graph_kernel_encoding_substituents_relative_positioning.pdf},
title = {Graph kernel encoding substituents relative positioning},
author = {Ga{"u}z{`e}re, Benoit and Brun, Luc and Villemin, Didier},
abstract = {Chemoinformatics aims to predict molecular properties using informational methods. Computer science's research fields concerned by this domain are machine learning and graph theory. An interesting approach consists in using graph kernels which allow to combine graph theory and machine learning frameworks. Graph kernels allow to define a similarity measure between molecular graphs corresponding to a scalar product in some Hilbert space. Most of existing graph kernels proposed in chemoinformatics do not allow to explicitly encode cyclic information, hence limiting the efficiency of these approaches. In this paper, we propose to define a cyclic representation encoding the relative positioning of substituents around a cycle. We also propose a graph kernel taking into account this information. This contribution has been tested on three classification problems proposed in chemoinformatics.},
affiliation = {Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen - GREYC , Laboratoire de chimie mol{'e}culaire et thioorganique - LCMT},
booktitle = {Proceedings of International Conference on Pattern Recognition (ICPR), 2014},
pages = {6 p.},
address = {Stockholm(SE)},
year = {2014},
month = Sep,
theme = "pattern,chemo"

 }

@article{RI-gauzere2014,


hal_id = {hal-01066295},
title = {Treelet kernel incorporating cyclic, stereo and inter pattern information in Chemoinformatics},
author = {Ga{"u}z{`e}re, Benoit and Grenier, Pierre-Anthony and Brun, Luc and Villemin, Didier},
keywords = {Chemoinformatics; Graph kernel; Machine learning},
language = {Anglais},
affiliation = {Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen - GREYC , Laboratoire de chimie mol{'e}culaire et thioorganique - LCMT},
volume=48,
number=2,
pages = {356-367},
journal = {Pattern Recognition},
audience = {international},
year = {2015},
month = "February",
url = {HAL :=http://hal.archives-ouvertes.fr/hal-01066295, Pdf := http://hal.archives-ouvertes.fr/hal-01066295/PDF/article.pdf},
abstract = {Chemoinformatics is a research field concerned with the study of physical or biological molecular properties through computer science's research fields such as machine learning and graph theory. From this point of view, graph kernels provide a nice framework which allows to naturally combine machine learning and graph theory techniques. Graph kernels based on bags of patterns have proven their efficiency on several problems both in terms of accuracy and computational time. Treelet kernel is a graph kernel based on a bag of small subtrees. We propose in this paper several extensions of this kernel devoted to chemoinformatics problems. These extensions aim to weight each pattern according to its influence, to include the comparison of non-isomorphic patterns, to include stereo information and finally to explicitly encode cyclic information into kernel computation.},
theme = {pattern,chemo}

 }

@inproceedings{CN-Gauzere2014c,


hal_id = {hal-00989071},
url = {Description := http://hal.archives-ouvertes.fr/hal-00989071, pdf:=http://hal.archives-ouvertes.fr/hal-00989071/PDF/rfia2014_submission_51.pdf},
title = {Repr{'e}sentation des cycles d'une mol{'e}cule sous forme d'hypergraphe},
author = {Ga{"u}z{`e}re, Benoit and Brun, Luc and Villemin, Didier},
abstract = {La ch{'e}moinformatique utilise des m{'e}thodes issues de la th{'e}orie des graphes et de l'apprentissage automatique afin de classifier ou pr{'e}dire des propri{'e}t{'e}s mol{'e}culaires. De ce point de vue, les noyaux sur graphes constituent une approche int{'e}ressante combinant les m{'e}thodes d'apprentissage et la repr{'e}sentation naturelle des mol{'e}cules sous forme de graphes. Cependant, bien que les graphes mol{'e}culaires encodent l'ensemble de l'information structurelle des mol{'e}cules, ils n'encodent pas explicitement l'information cyclique. Dans cet article, nous proposons de repr{'e}senter une mol{'e}cule par un hypergraphe encodant explicitement {`a} la fois l'information cyclique et acyclique d'une mol{'e}cule dans une m{^e}me repr{'e}sentation. Nous proposons {'e}galement une mesure de similarit{'e} sous forme de noyau afin d'utiliser cette repr{'e}sentation mol{'e}culaire dans des probl{`e}mes rencontr{'e}s en ch{'e}moinformatique.},
booktitle = {Actes de la conf{'e}rence RFIA 2014},
address = {Rouen, France},
audience = {nationale },
year = {2014},
month = Jun,
theme = {pattern,chemo}

 }

@inproceedings{CI-grenier2014c,


hal_id = {hal-00988762},
url = {Description := http://hal.archives-ouvertes.fr/hal-00988762, pdf:= http://hal.archives-ouvertes.fr/hal-00988762/PDF/rfia2014_submission_88.pdf},
title = {{Un noyau sur graphe prenant en compte la st{'e}r{'e}oisom{'e}rie des mol{'e}cules}},
author = {Grenier, Pierre-Anthony and Brun, Luc and Villemin, Didier},
abstract = {{L'{'e}tude des relations quantitatives structure-activit{'e} (QSAR) ou structure-propri{'e}t{'e} (QSPR) sont deux domaines de recherche actifs, o{`u} le but est la pr{'e}diction de propri{'e}t{'e}s de mol{'e}cules. Dans ces domaines, les noyaux sur graphes permettent de combiner la repr{'e}sentation naturelle des mol{'e}cules par des graphes avec des m{'e}thodes classiques d'apprentissage automatique tels que les machines {`a} vecteurs de support. Malheureusement, le positionnement relatif des atomes dans l'espace peut {^e}tre diff{'e}rent pour des mol{'e}cules repr{'e}sent{'e}es par un m{^e}me graphe, ces mol{'e}cules peuvent donc avoir des propri{'e}t{'e}s diff{'e}rentes. Ces mol{'e}cules sont appel{'e}es st{'e}r{'e}oisom{`e}res. Les propri{'e}t{'e}s variant entre les st{'e}r{'e}oisom{`e}res ne peuvent pas {^e}tre pr{'e}dites par les m{'e}thodes habituelles bas{'e}es sur des graphes simples. Dans cet article, nous pr{'e}sentons une nouvelle repr{'e}sentation des mol{'e}cules qui prend en compte la st{'e}r{'e}oisom{'e}rie et nous proposons un noyau entre ces structures permettant de pr{'e}dire des propri{'e}t{'e}s li{'e}es {`a} la st{'e}r{'e}oisom{'e}rie.}},
booktitle = {{Actes de la conf{'e}rence RFIA 2014}},
address = {France},
year = {2014},
month = Jun,
theme = {pattern,chemo},

 }

@inproceedings{CI-Grenier2014b,


hal_id = {hal-01059530},
title = {{A Graph Kernel incorporating molecule's stereisomerism information}},
author = {Grenier, Pierre-Anthony and Brun, Luc and Villemin, Didier},
abstract = {{The prediction of molecule's properties through Quantitative Structure Activity (resp. Property) Relationships are two active research fields named QSAR and QSPR. Within these frameworks Graph kernels allow to combine a natural encoding of a molecule by a graph with classical statistical tools such as SVM or kernel ridge regression. Unfortunately some molecules encoded by a same graph and differing only by the three dimensional orientations of their atoms in space have different properties. Such molecules are called stereoisomers. These latter properties can not be predicted by usual graph methods which do not encode stereoisomerism. In this paper we propose a new graph encoding of molecules taking explicitly into account stereoisomerism and propose a new kernel between these structures in order to predict properties related to stereoisomerism.}},
booktitle = {{Proceedings of ICPR 2014}},
pages = {-},
address = {Stockholm, Su{`e}de},
year = {2014},
month = Aug,
url = {HAL:=http://hal.archives-ouvertes.fr/hal-01059530},
theme="pattern,chemo"

 }

@inproceedings{CI-Grenier2014,


author = {Pierre{-}Anthony Grenier and
Luc Brun and Didier Villemin},
title = {Incorporating Molecule's Stereisomerism within the Machine Learning Framework},
booktitle = {Structural, Syntactic, and Statistical Pattern Recognition - Joint{IAPR} International Workshop, {S+SSPR} 2014. Proceedings},
address ={Joensuu, Finland},
month ={August 20-22},
year = {2014},
pages = {12--21},
theme = "pattern,chemo",
doi = {10.1007/978-3-662-44415-3_2},
url ={LNCS:=http://dx.doi.org/10.1007/978-3-662-44415-3_2, HAL:=http://hal.archives-ouvertes.fr/docs/01/05/95/21/PDF/article.pdf}

 }

@inproceedings{Mahboubi2014,


author = {Amal Mahboubi and
Luc Brun and
Donatello Conte and
Pasquale Foggia and
Mario Vento},
title = {Tracking System with Re-identification Using a {RGB} String Kernel},
booktitle = {Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2014. Proceedings},
address ={Joensuu, Finland},
month ={August 20-22},
year = {2014},
pages = {333--342},
doi = {10.1007/978-3-662-44415-3_34},
theme = "pattern"

 }

@inproceedings{CI-Gauzere2014,


author = {Benoit Ga{"{u}}z{`{e}}re and
S{'{e}}bastien Bougleux and
Kaspar Riesen and
Luc Brun},
title = {Approximate Graph Edit Distance Guided by Bipartite Matching of Bags of Walks},
booktitle = {Structural, Syntactic, and Statistical Pattern Recognition - Joint{IAPR} International Workshop, {S+SSPR} 2014. Proceedings},
address ={Joensuu, Finland},
month ={August 20-22},
year = {2014},
pages = {73--82},
url = {DOI:=http://dx.doi.org/10.1007/978-3-662-44415-3_8, HAL:=http://hal.archives-ouvertes.fr/hal-01066384, Pdf:= http://hal.archives-ouvertes.fr/docs/01/06/63/84/PDF/ssspr2014_submission_59.pdf},
theme = "pattern,chemo,ged"

 }

@InBook{CL-Gauzere2014,


author = {Benoit GaÃ¼zÃ¨re and Luc Brun and Didier Villemin},
title = {Quantitative Graph Theory: Mathematical Foundations and Applications},
chapter = {Graph kernels in chemoinformatics},
publisher = {CRC Press},
year = 2014,
series = {Discrete Mathematics and Its Applications},
theme= "pattern,chemo",
url = {Draft version(pdf):=https://brunl01.users.greyc.fr/ARTICLES/BookGraphKernel.pdf}

 }

@inproceedings{CI-Brun2013,


title = {Learning and classification of car trajectories in road video by string kernels},
author = {Luc Brun and Alessia Saggese and Mario Vento},
year = {2013},
date = {2013-01-01},
booktitle = {Proceedings of the International Conference on Computer Vision Theory and Applications (V.I.S.A.P.P)},
address={Barcelona, Spain},
pages = {709-714},
keywords = {Video analysis and interpretation},
theme="pattern",
abstract= {An abnormal behavior of a moving vehicule or a moving
person is characterized by an unusual or not
expected trajectory. The definition of exptected
trajectories refers to supervised learning where an
human operator should define expected
behaviors. Conversely, definition of usual
trajectories, requires to learn automatically the
dynamic of a scene in order to extract its typical
trajectories. We propose, in this paper, a method
able to identify abnormal behaviors based on a new
unsupervised learning algorithm. The original
contributions of the paper lies in the following
aspects: first, the evaluation of similarities
between trajectories is based on string
kernels. Such kernels allow us to define a
kernel-based clustering algorithm in order to obtain
groups of similar trajectories. Finally,
identification of abnormal trajectories is performed
according to the typical trajectories characterized
during the clustering step. The method has been
evaluated on a real dataset and comparisons with
other state-of-the-arts methods confirm its
efficiency.},
url= {paper:=https://brunl01.users.greyc.fr/ARTICLES/visapp2013.pdf}

 }

@Article{RI-brun-2014,


author = {Luc Brun and Alessia Saggese and Mario Vento},
title = {Dynamic Scene Understanding for behavior analysis based on string kernels},
journal = {Circuits and Systems for Video Technology, IEEE Transactions on},
year = 2014,
volume = {24},
number = 10,
pages = {1669 - 1681},
theme = "pattern",
abstract={This work aims at dynamically understanding the properties
of a scene from the analysis of moving object
trajectories. Two different applications are
proposed: the first one is devoted to identify
abnormal behaviors, while the latter allows to
extract the k most similar trajectories to the one
handdrawn by an human operator. A set of normal
trajectoriesâ models is extracted by means of a
novel unsupervised learning technique: the scene is
adaptively partitioned into zones by using the
distribution of the training set and each trajectory
is represented as a sequence of symbols by taking
into account positional information (the zones
crossed in the scene), speed and shape. The main
novelties are the following: first, the use of a
kernel based approach for evaluating the similarity
between trajectories. Furthermore, we define a novel
and efficient kernelbased clustering algorithm,
aimed at obtaining groups of normal
trajectories. Experimentations, conducted over three
standard datasets, confirm the effectiveness of the
proposed approach.},
url={TR(pdf):= https://brunl01.users.greyc.fr/ARTICLES/TR_traj_string_kernel.pdf}

 }

@inproceedings{CN-gauzere-2013,


title = {A new hypergraph molecular representation},
author = {GaÃ¼zÃ¨re, Benoit and Brun, Luc and Villemin, Didier},
abstract = {In this contribution, we define a new molecular representation together with a similarity measure which allows to encode adjacency relationships between cycles and their substituents.},
language = {Anglais},
affiliation = {Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen - GREYC , Laboratoire de chimie moleculaire et thioorganique - LCMT},
booktitle = {Actes des 6 iemes Journees de la Chemoinformatique.},
pages = {1},
address = {Nancy, France},
audience = {internationale },
year = {2013},
month = Oct,
theme="pattern,chemo",
url = {abstract:=http://hal.archives-ouvertes.fr/hal-00867298,pdf := http://hal.archives-ouvertes.fr/hal-00867298/PDF/article.pdf}

 }

@inproceedings{CN-grenier-2013,


title = {{Chiral Kernel : Taking into account stereoisomerism}},
author = {Grenier, Pierre-Anthony and Brun, Luc and Villemin, Didier},
keywords = {Chemoinformatics; Graph kernel; Chirality},
language = {Anglais},
affiliation = {Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen - GREYC , Laboratoire de chimie mol{'e}culaire et thioorganique - LCMT},
booktitle = {6emes journees de la Societe Francaise de Chemoinformatique (SFCi)},
address = {Nancy, France},
audience = {nationale },
year = {2013},
month = Oct,
theme="pattern,chemo",
abstract = {Graph kernels provides a framework combining machine learning and graph theory. However, kernels based upon the molecular graph, which can not distinguish stereoisomers, are unable to predict properties which differs among stereoisomers. This article presents a graph kernel which takes into account chirality, and is used (in combination with a classical graph kernel) to predict the optical rotation of molecules.},
url = {HAL :=http://hal.archives-ouvertes.fr/hal-00864278,PDF := http://hal.archives-ouvertes.fr/hal-00864278/PDF/article.pdf},

 }

@InProceedings{jaume-2013,


author = {Jaume Gibert and Ernest Valveny and Horst Bunke and Luc Brun},
title = {Graph Clustering Through Attribute Statistics Based
Embedding},
booktitle = {Computer Analysis Images and Patterns 2013},
year = 2013,
month = {August},
address = {York},
editor = {R. Wilson and E. Hancock and A. Bors and W. Smith},
pages= {302-309},
volume = {lncs 8047},
theme= "pattern",
url = {Pdf := https://brunl01.users.greyc.fr/ARTICLES/CAIP2013-Embedding.pdf}

 }

@InProceedings{mahboubi-2013b,


author = {Amal MAHBOUBI and Luc BRUN and Donatello CONTE and Pasquale FOGGIA and Mario VENTO},
title = {Re-identification de Personnes par Modele de Noyaux de Graphe},
booktitle = {GRETSI 2013},
year = 2013,
month = {September},
address = {Brest},
theme = "pattern"

 }

@InProceedings{amal-2013,


author = {Amal Mahboubi and Luc Brun and Donatello Conte and Pasquale Foggia and Mario Vento},
title = {Tracking System with Re-identification Using a Graph Kernels
Approach},
booktitle = {Computer Analysis Images and Patterns 2013},
year = 2013,
month = {August},
address = {York},
editor = {R. Wilson and E. Hancock and A. Bors and W. Smith},
pages= {401-408},
volume = {lncs 8047},
theme= "pattern",
abstract= "This paper addresses people re-identification
problem for visual surveillance applications. Our
approach is based on a rich description of each
occurrence of a person thanks to a graph encoding of
its salient points. The appearance of persons in a
video is encoded by bags of graphs whose
similarities are encoded by a graph kernel. Such
similarities combined with a tracking system allow
us to distinguish a new person from a re-entering
one into the video. The efficiency of our method is
demonstrated through experiments.",
url = {Pdf := https://brunl01.users.greyc.fr/ARTICLES/caip_amal_2013.pdf}

 }

@inproceedings{CI-conte-2013,


author = {Donatello Conte and
Jean-Yves Ramel and
Nicolas Sidere and
Luqman, Muhammad Muzzamil and
Benoit Ga{"u}z{`e}re and
Jaume Gibert and
Luc Brun and
Mario Vento},
title = {A Comparison of Explicit and Implicit Graph Embedding Methods
for Pattern Recognition},
booktitle = {Graph-Based Representations in Pattern Recognition - 9th
IAPR-TC-15 International Workshop},
year = {2013},
pages = {81-90},
ee = {http://dx.doi.org/10.1007/978-3-642-38221-5_9},
theme = "pattern",
url = {Abstract and Pdf := http://hal.archives-ouvertes.fr/hal-00829226}

 }

@Article{RN-Gauzere-2012,


author = {Benoit GaÃ¼zÃ¨re and Luc Brun and Didier Villemin},
title = {Noyau de Treelets appliqu'e aux graphes 'etiquet'es et aux graphes de cycles},
journal = {Revue d'Intelligence Artificielle},
year = 2013,
volume = 27,
number = 1,
pages = {121-144},
abstract= "La ch'emoinformatique utilise des m'ethodes issues de
lâinformatique, plus particuliÃ¨rement la th'eorie des
graphes et lâapprentissage automatique, aï¬n de
classiï¬er ou pr'edire les propri'et'es de bases de
mol'ecules. Dans ce contexte, les noyaux sur graphes
fournissent une approche int'eressante en combinant
les m'ethodes dâapprentissage automatique et la
repr'esentation naturelle des mol'ecules par
graphes. Parmi les m'ethodes bas'ees sur les noyaux
sur graphes, la d'ecomposition du graphe en
sous-structures repr'esente une importante famille de
noyau. Dans cet article, nous pr'esentons deux
extensions dâun noyau pr'ec'edemment bas'e sur les
sous-structures non 'etiquet'ees Ã  lâ'enum'eration de
sous structures 'etiquet'ees et Ã  la prise en compte
de lâinformation cyclique des mol'ecules. Nous
proposons 'egalement des m'ethodes de s'election de
variables permettant de pond'erer un ensemble de
sous-structures aï¬n dâam'eliorer la pr'ecision de la
pr'ediction.",
theme="pattern,chemo",
url={RIA Online := http://ria.revuesonline.com/article.jsp?articleId=18201,HAL:=http://hal.archives-ouvertes.fr/hal-00847279}

 }

@inproceedings{CI-gauzere-2013-2,


hal_id = {hal-00829227},
title = {{Relevant Cycle Hypergraph Representation for Molecules}},
author = {Ga{"u}z{`e}re, Benoit and Brun, Luc and Villemin, Didier},
abstract = {Chemoinformatics aims to predict molecule's properties through informational methods. Some methods base their prediction model on the comparison of molecular graphs. Considering such a molecular representation, graph kernels provide a nice framework which allows to combine machine learning techniques with graph theory. Despite the fact that molecular graph encodes all structural information of a molecule, it does not explicitly encode cyclic information. In this paper, we propose a new molecular representation based on a hypergraph which explicitly encodes both cyclic and acyclic information into one molecular representation called relevant cycle hypergraph. In addition, we propose a similarity measure in order to compare relevant cycle hypergraphs and use this molecular representation in a chemoinformatics prediction problem.},
language = {Anglais},
affiliation = {Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen - GREYC , Laboratoire de chimie mol{'e}culaire et thioorganique - LCMT},
booktitle = {Graph-Based Representations in Pattern Recognition},
pages = {111},
address = {Autriche},
audience = {internationale },
year = {2013},
month = May,
url = {Abstract:= http://hal.archives-ouvertes.fr/hal-00829227,pdf:=http://hal.archives-ouvertes.fr/hal-00829227/PDF/GbR2013_014.pdf},
theme="pattern",

 }

@inproceedings{CI-grenier-2013,


hal_id = {hal-00824172},
title = {{Treelet Kernel Incorporating Chiral Information}},
author = {Grenier, Pierre-Anthony and Brun, Luc and Villemin, Didier},
abstract = {{Molecules being often described using a graph representation, graph kernels provide an interesting framework which allows to combine machine learning and graph theory in order to predict molecule's properties. However, some of these properties are induced both by relationships between the atoms of a molecule and by constraints on the relative positioning of these atoms. Graph kernels based solely on the graph representation of a molecule do not encode this relative positioning of atoms and are consequently unable to predict accurately some molecule's properties. This paper presents a new method which incorporates spatial constraints into the graph kernel framework in order to overcome this limitation.}},
keywords = {Graph kernel; Chemoinformatics; Chirality},
language = {Anglais},
affiliation = {Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen - GREYC , Laboratoire de chimie mol{'e}culaire et thioorganique - LCMT},
booktitle = {{9th IAPR-TC15 International Workshop on Graph-based Representations in Pattern Recognition}},
address = {Vienne, Autriche},
audience = {internationale },
year = {2013},
month = May,
url = {Abstact:=http://hal.archives-ouvertes.fr/hal-00824172,PDF:=http://hal.archives-ouvertes.fr/hal-00824172/PDF/article.pdf},
theme="pattern,chemo"

 }

@Article{PRL2012,


author = {Benoit GaÃ¼zÃ¨re and Luc Brun and Didier Villemin},
title = {Two new graphs kernels in chemoinformatics},
journal = {Pattern Recognition Letters},
year = 2012,
issn = "0167-8655",
doi = "10.1016/j.patrec.2012.03.020",
url = "ScienceDirect:=http://www.sciencedirect.com/science/article/pii/S016786551200102X, HAL := http://hal.archives-ouvertes.fr/hal-00773283",
keywords = "Chemoinformatics",
keywords = "Graph kernel",
keywords = "Machine learning",
abstract = "Chemoinformatics is a well established research field
concerned with the discovery of moleculeâs
properties through informational
techniques. Computer scienceâs research fields
mainly concerned by chemoinformatics are machine
learning and graph theory. From this point of view,
graph kernels provide a nice framework combining
machine learning and graph theory techniques. Such
kernels prove their efficiency on several
chemoinformatics problems and this paper presents
two new graph kernels applied to regression and
classification problems. The first kernel is based
on the notion of edit distance while the second is
based on subtrees enumeration. The design of this
last kernel is based on a variable selection step in
order to obtain kernels defined on parsimonious sets
of patterns. Performances of both kernels are
investigated through experiments.",
theme="pattern,chemo",
volume=33,
number=15,
pages={2038-2047}

 }

@inproceedings{sitis2012,


title = {A clustering algorithm of trajectories for behaviour understanding based on string kernels},
author = {Luc Brun and Alessia Saggese and Mario Vento},
year = {2012},
date = {2012-11-28},
booktitle = {Proceedings of the Conference on Signal Image Technology & Internet Based Systems (SITIS)},
address={Sorrento, Italy},
pages = {267--274},
publisher = {IEEE},
keywords = {Video analysis and interpretation},
theme="pattern",
url={Abstract and Pdf := http://hal.archives-ouvertes.fr/hal-00768648}

 }

@InProceedings{CI-gauzere-2012,


author = {Benoit GaÃ¼zÃ¨re and Luc Brun and Didier Villemin},
title = {Graph Kernels Based on Relevant Patterns and Cycle Information for Chemoinformatics},
booktitle = {Proceedings of ICPR 2012},
address = {Tsukuba, Japan},
year = 2012,
month = {November},
organization = {IAPR},
publisher = {IEEE},
pages= {1775-1778},
theme="pattern,chemo",
url ={Abstract and Pdf := http://hal.archives-ouvertes.fr/hal-00768652}

 }

@InProceedings{CI-Bougleux-2012,


author = {SÃ©bastien Bougleux and Francois-Xavier Dup'e and Luc Brun and GaÃ¼zÃ¨re Benoit and Myriam Mokhtari},
title = {Shape Similarity based on Combinatorial Maps and a Tree Pattern Kernel},
booktitle = {Proceedings of ICPR 2012},
address = {Tsukuba, Japan},
year = 2012,
volume = 7626,
month = {November},
organization = {IAPR},
publisher = {IEEE},
pages={1602-1605},
address={Tsukuba, Japan},
theme="pattern",
url ={Abstract and Pdf := http://hal.archives-ouvertes.fr/hal-00768662}

 }

@InProceedings{CI-gauzere-2012-2,


author = {Benoit GaÃ¼zÃ¨re and Hasegawa Makoto and Luc Brun and Salvatore Tabbone},
title = {Implicit and Explicit Graph Embedding: Comparison of both Approaches on Chemoinformatics Applications.},
booktitle = {Proceedings of S+SSPR2012},
address={Miyajima-Itsukushima, Hiroshima, Japan},
year = 2012,
editor = {A. Imiya et al.},
volume = 7626,
series = {LNCS},
month = {November},
organization = {IAPR TC 2},
publisher = {Springer},
pages= {510-518},
theme="pattern",
url = {Abstract and Pdf :=http://hal.archives-ouvertes.fr/hal-00768654}

 }

@InProceedings{CI-Bougleux-2012b,


author = {SÃ©bastien Bougleux and Francois-Xavier Dup'e and Luc Brun and Myriam
Mokhtari},
title = {Shape Similarity based on a Treelet Kernel with Edition},
booktitle = {Proceedings of S+SSPR2012},
address={Miyajima-Itsukushima, Hiroshima, Japan},
year = 2012,
editor = {A. Imiya et al.},
volume = 7626,
pages= {199-207},
series = {LNCS},
month = {November},
organization = {IAPR TC 2},
publisher = {Springer},
theme="pattern",
url ={Abstract and Pdf := http://hal.archives-ouvertes.fr/hal-00768661},

 }

@InProceedings{CI-gauzere-2012-3,


author = {Benoit GaÃ¼zÃ¨re and Luc Brun and Didier Villemin},
title = {Graph Kernels: Crossing Information from Different Patterns using Graph Edit Distance},
booktitle = {Proceedings of S+SSPR2012},
address={Miyajima-Itsukushima, Hiroshima, Japan},
year = 2012,
editor = {A. Imiya et al.},
volume = 7626,
series = {LNCS},
pages= {42-50},
month = {November},
organization = {IAPR TC 2},
publisher = {Springer},
theme="pattern,chemo",
url={Abstract and Pdf := http://hal.archives-ouvertes.fr/hal-00768658}

 }

@InProceedings{CN-GAUZERE-2011a,


author = {Benoit GaÃ¼zÃ¨re and Luc Brun and Didier Villemin},
title = {Deux nouveaux noyaux sur Graphes et leurs applications en chimioinformatique},
booktitle = {Apprentissage et Graphes pour les Syst`emes complexes (AGS) 2011},
year = 2011,
month = {May},
organization = {AFIA},
pages={28-39},
url = {Abstract and Pdf :=http://hal.archives-ouvertes.fr/hal-00596513},
theme="pattern,chemo"

 }

@InProceedings{CN-GAUZERE-2012,


author = {Benoit GaÃ¼zÃ¨re and Luc Brun and Didier Villemin},
title = {Noyau de Treelets Appliqu'e aux Graphes 'Etiquet'es},
booktitle = {Actes de RFIA 2012},
year = 2012,
month = {Jan.},
organization = {AFRIF},
address = {Lyon, France},
note = {Actes en ligne accessibles sous HAL},
url = {paper (pdf):=http://hal.archives-ouvertes.fr/hal-00656519/PDF/rfia2012_submission_96.pdf},
abstract = "La ch'emoinformatique utilise des m'ethodes issues de lâinformatique,
plus particuliÃ¨rement la th'eorie des graphes et
lâapprentissage automatique, afin de classifier ou pr'edire
les propri'et'es de bases de mol'ecules. Dans ce contexte, les
noyaux sur graphes fournissent une approche int'eressante
en combinant les m'ethodes dâapprentissage automatique et
la repr'esentation naturelle des mol'ecules par graphes. Plusieurs
m'ethodes bas'ees sur les noyaux sur graphes ont 'et'e
propos'ees pour r'esoudre des problÃ¨mes en ch'emoinformatique.
La d'ecomposition du graphe en sous structures repr'esente
une importante famille de noyau. Dans cet article,
nous pr'esentons une extension dâun noyau pr'ec'edemment
bas'e sur les sous structures non 'etiquet'ees Ã  lâ'enum'eration
de sous structures 'etiquet'ees. Nous proposons 'egalement
deux m'ethodes it'eratives permettant de s'electionner un ensemble
de sous structures afin dâam'eliorer la pr'ecision de
la pr'ediction. Le noyau a 'et'e valid'e sur deux jeux de donn'ees
impliquant des graphes 'etiquet'es.",
theme="pattern,chemo"

 }

@inproceedings{CI-GAUZERE-2011,


author = {Benoit GaÃ¼zÃ¨re and Luc {Brun} and Didier {Villemin}},
title = {Two new Graph Kernels and Applications to Chemoinformatics},
booktitle = {In 8th IAPR - TC-15 Workshop on Graph-based
Representations in Pattern Recognition (GBR'11)},
publisher = {Springer},
editor = {Xiaoyi {Jiang} and Miquel {Ferrer} and Andrea {Torsello}},
series = {Lecture Notes in Computer Science},
volume = {6658},
pages = {112-122},
year = {2011},
month = {May},
url = {Abstract and Pdf :=http://hal.archives-ouvertes.fr/docs/00/59/65/06/PDF/article.pdf},
keywords = {Graph kernels},
theme={pattern,chemo}

 }

@inproceedings{CI-BRUN-2011,


author = {Luc {Brun} and Donatello Conte and Pasquale Foggia and Mario Vento},
title = {A graph kernel method for Re-identification},
booktitle = {In 8th International Conference on Image Analysis and
Recognition (ICIAR'2011)},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
year = {2011},
month = {June},
pages={173-182},
volume={6753},
keywords = {Graph kernels,Video analysis},
theme={pattern},
url={HAL:= http://hal.archives-ouvertes.fr/hal-00770260, pdf:=http://hal.archives-ouvertes.fr/docs/00/77/02/60/PDF/ICIAR2011.pdf}

 }

@inproceedings{CI-BRUN-2011,


author = {Luc {Brun} and Donatello Conte and Pasquale Foggia and Mario Vento},
title = {People Re-identification by Graph Kernel Methods},
booktitle = {In 8th IAPR - TC-15 Workshop on Graph-based
Representations in Pattern Recognition (GBR'11)},
publisher = {Springer},
editor = {Xiaoyi {Jiang} and Miquel {Ferrer} and Andrea {Torsello}},
series = {Lecture Notes in Computer Science},
volume = {6658},
pages = {285-294},
year = {2011},
month = {May},
url = {Abstract and Pdf :=http://hal.archives-ouvertes.fr/hal-00680229},
keywords = {Graph kernels},
theme={pattern}

 }

@InProceedings{CI-BRUN-2010,


author = {Luc Brun and Donatello Conte and Pasquale Foggia and Mario Vento and Didier Villemin},
title = {Symbolic Learning vs. Graph Kernels: An Experimental Comparison in a Chemical Application},
booktitle = {Proceedings of the First International Workshop on Querying Graph Structured Data},
year = 2010,
address = {Novi Sad, Serbia},
month = {September},
publisher = {Springer},
theme={pattern},
url={paper(pdf) := https://brunl01.users.greyc.fr/ARTICLES/GraphQ2010BrunConte.pdf},
abstract = "In this paper we present a quantitative comparison
between two approaches, Graph Kernels and
Symbolic Learning, within a classification scheme.
The experimental case-study is the predictive
toxicology evaluation, that is the inference of the
toxic characteristics of chemical compounds from
their structure. The results demonstrate that both
approaches are comparables in terms of accuracy, but
present pros and cons that are discussed in the last
part of the paper."

 }

@InProceedings{ACTI-DUPE-2010,


author = {Francois-Xavier Dup{'e} and S{'e}ebastien Bougleux and Luc Brun and Olivier Lezoray and Abder Elmoataz},
title = {Kernel Based Implicit Graph Regularization of Structured Objects},
booktitle = {Proc. of ICPR'2010},
year = 2010,
month = {August},
organization = {IAPR},
theme = {shape,pattern},
url= {paper(pdf) :=https://brunl01.users.greyc.fr/ARTICLES/icpr2010Dupe.pdf},
abstract = "Weighted Graph regularization provides a rich framework
which allow to regularize functions defined over the
vertice of a weighted graph. Until now, such a
framework has been only defined for real or
multivalued functions hereby restricting the
regularization framework to numerical objects. On
the other hand, several kernels have been defined on
structured objects such as strings or graphs. Using
definite positive kernels, each original object is
associated by the ``kernel trick'' to one element of
an Hilbert space. This paper proposes to extend the
weighted graph regularization framework to objects
implicitly defined by their kernel hereby performing
the regularization within the Hilbert space
associated to the kernel. This work opens the door
to the regularization of structured objects."

 }

@InProceedings{CN-DUPE-2009,


author = {Francois-Xavier Dup'e and Luc Brun},
title = {Classification de formes avec un noyau sur graphes flexible et robuste au bruit},
booktitle = {Proceedings of RFIA'2010},
year = 2010,
address = {Caen},
month = {January},
organization = {AFRIF},
theme={shape,pattern},
url={papier(pdf) := https://brunl01.users.greyc.fr/ARTICLES/RFIA2010DupeBrun.pdf},
abstract={La squelettisation par axe median 'etant
une transformation homotopique, le squelette d'une forme 2D
correspond Ã  un graphe planaire dont les faces codent les trous et
les sommets chaque jonction et extr'emit'e. Ce graphe n'est pas un
graphe simple, car compos'e de boucles internes et d'arÃªtes multiples
a cause des trous. Dans le cadre de la comparaison de formes,
celui-ci est souvent transform'e en une structure plus simple comme
un arbre ou un graphe simple, perdant de ce fait des informations
importantes sur la forme. Dans ce papier, nous proposons un noyau
sur graphes combinant un noyau sur sacs de chemins et un noyau sur
faces. Les chemins sont d'efinis Ã  partir du graphe non simple et le
noyau sur chemins est renforc'e par un processus d''edition. Le noyau
sur faces reflÃ¨te l'importance des trous dans une forme, cette
information pouvant Ãªtre une caract'eristique importante de la
forme. Le noyau r'esultant est un noyau d'efini positif, comp'etitif
avec les noyaux propos'es dans l''etat de l'art. }


 }

@inproceedings{CI-ROSENBERGER-2008-1,


author={Christophe Rosenberger and Luc Brun},
title={Similarity-Based Matching for Face Authentication},
booktitle={Proceedings of the International Conference on Pattern Recognition (ICPR'2008)},
year={2008},
address={Tampa, Florida, USA},
pages={0-0},
theme={pattern}

 }

@InProceedings{CI-DUPE-2008-2,


author = {Dup'e, F.-X. and Brun, L.},
title = {Hierarchical Bag of Paths for Kernel Based Shape Classification},
booktitle = {Proceedings of S+SSPR 2008},
pages = {227-236} ,
year = {2008},
theme= {shape,pattern},
address = {Orlando},
abstract={Graph kernels methods are based on an implicit embedding of graphs
within a vector space of large dimension. This implicit embedding
allows to apply to graphs methods which where until recently solely
reserved to numerical data. Within the shape classification
framework, graphs are often produced by a skeletonization step which
is sensitive to noise. We propose in this paper to integrate the
robustness to structural noise by using a kernel based on a bag of
path where each path is associated to a hierarchy encoding
successive simplifications of the path. Several experiments prove
the robustness and the flexibility of our approach compared to
alternative shape classification methods.},
url={paper(pdf):=https://brunl01.users.greyc.fr/ARTICLES/sspr2008.pdf, arXiv:=https://arxiv.org/abs/0810.3579}

 }

@Misc{BR-LEBOSSE-2006,


author = {J'erome Leboss'e and Jean-Claude Pailles},
title = {D'etermination d'identification de signal},
institution = {France T'el'ecom},
year = {2006},
theme= {fingerprint},
note= {Brevet 06 50403}

 }

@InProceedings{CI-LEBOSSE-2007,


author = {Jerome Leboss{'e} and Luc Brun},
title = {Audio Fingerprint Identification by Approximate String Matching},
booktitle = {Proceedings of ISMIR 2007},
url = {pdf (see the conference site) := http://ismir2007.ismir.net/schedule.html},
theme= {fingerprint},
year = 2007,
address = {Vienna (Austria)},
month = {September}

 }

@InProceedings{CN-LEBOSSE-2006,


author = {J'erome Leboss'e and Luc Brun and Pailles, Jean Claude},
title = {Fingerprint audio robuste pour la gestion de droits},
booktitle = {Actes de CORESA 2006},
year = 2006,
address = {Caen},
month = {Novembre},
theme= {fingerprint},
abstract= "Le fingerprint audio permet d'identifier un
document audio {'e}ventuellement corrompu, {`a} partir
d'un court extrait. Ces m{'e}thodes peuvent {^e}tre
utilis{'e}es dans le cadre de la gestion des droits
num{'e}riques (DRM) dans le but d'associer les
informations de gestion et de contr{^o}le {`a} chaque
document. Dans cet article, nous proposons un
nouveau mode de calcul de fingerprint audio qui
combine une m{'e}thode de segmentation avec un nouveau
sch{'e}ma de construction des codes d{'e}finissants le
fingerprint. La m{'e}thode propos{'e}e est robuste aux
alt{'e}rations du document audio telles la compression
et la suppression de parties ou d{'e}calages
temporels.",
url = {article(pdf):=https://brunl01.users.greyc.fr/ARTICLES/CORESA_16_05.pdf}

 }

@InProceedings{CI-Lebosse-2007,


author = {J'erome Leboss'e and Luc Brun and Pailles, Jean Claude},
title = {A Robust Audio Fingerprint's Based Identification Method},
booktitle = {Proceedings of IbPRIA'2007},
pages = {185-192},
year = 2007,
editor = {Joan Marti and Benedi, Jose Miguel and Mendonca, Ana Maria and Serrat, Joan},
volume = {I},
number = 4477,
address = {Girona},
month = {June},
publisher = {LNCS},
theme= {fingerprint},
abstract= "An audio fingerprint is a small digest of an audio file
computed from its main perceptual properties. Like human
fingerprints, audio fingerprints allow to identify an
audio file among a set of candidates but does not allow to
retrieve any other characteristics of the
files. Applications of audio fingerprint include audio
monitoring on broadcast chanels, filtering peer to peer
networks, meta data restoration in large audio library and
the protection of author's copyrights within a Digital
Right Management(DRM) system. We propose in this paper a
new fingerprint extraction algorithm based on a new audio
segmentation method. A scoring function based on q-grams
is used to determine if an input signal is a derivated
version of a fingerprint stored in the database. A rule
based on this scoring function allows to either recover
the original input file or to decide that no fingerprint
belonging to the database correspond to the signal. The
proposed method is robust against compression and time
shifting alterations of audio files.",
url = {article(ps):=https://brunl01.users.greyc.fr/ARTICLES/ibpria2007.ps}


 }

@InProceedings{CN-Lebosse-2007,


author = {J'erome Leboss'e and Luc Brun and Pailles, Jean Claude},
title = {Identification de signaux audio par appariement de ch^{i}nes},
booktitle = {Proc. of GRETSI 2007},
year = {2007},
address = {Troyes, France},
month = {September},
theme= {fingerprint},
abstract= "Nous proposons une m{'e}thode d'identification
bas{'e}e {`a} la fois sur une d{'e}coupe adaptative du
signal et sur un traitement des erreurs de
segmentation {`a} l'aide d'une fonction de
similarit{'e} entre chaines.La fonction de
similarit{'e} que nous proposons permet {`a} la fois
d'identifier un fichier lorsqu'il est pr{'e}sent et
de tester sa pr{'e}sence dans la base. ",
url = {article(pdf):=https://brunl01.users.greyc.fr/ARTICLES/gretsi.pdf}

 }

@PhdThesis{TH-Lebosse-2009,


author = {Jerome Leboss'e},
title = {M'ethodes d'identification pour le controle de l'utilisation de documents audio},
school = {Universit'e de Caen},
year = 2009,
month = {May},
url ={manuscript(pdf):=https://brunl01.users.greyc.fr/ARTICLES/TheseJerome.pdf},
theme= {fingerprint},
abstract= "L'objectif de ces travaux de recherche est de proposer
une m'ethode fiable et robuste d'identification de documents audio et
plus particuliÃ¨rement musicaux. Les contraintes de cette m'ethode sont
nombreuses puisque nous d'esirons une m'ethode avec un fort pouvoir
discriminant qui soit capable d'identifier un document audio
parallÃ¨lement Ã  sa lecture, qui requiÃ¨re de faibles capacit'es de
stockage et soit robuste vis Ã  vis de certaines alt'erations du
signal. Nous avons donc conÃ§u une m'ethode d'identification de signaux
audio bas'ee sur l'extraction d'une empreinte. Cette empreinte permet
de reconnaÃ®tre un signal parmi un ensemble de signaux caract'eris'es par
leurs empreintes. Pour cela, l'empreinte est calcul'ee Ã  partir de
certaines propri'et'es du signal. L'originalit'e de notre m'ethode vient
du fait que la plupart des m'ethodes existantes se basent sur une
analyse des fr'equences. Or notre m'ethode se base uniquement sur une
analyse temporelle du signal et l'extraction de positions remarquables
(onsets) Ã  l'int'erieur de celui-ci. Les mesures de similarit'e que nous
proposons utilisent les sp'ecificit'es de nos empreintes pour identifier
de faÃ§on pr'ecise des documents tout en conservant de faibles temps de
calculs malgr'e la taille et le nombre de nos empreintes. Ce m'emoire
d'ecrira les deux 'etapes conduisant Ã  l'identification d'un extrait
audio inconnu, Ã  savoir une premiÃ¨re phase de calcul d'empreinte et
une seconde de comparaison avec un ensemble d'empreintes pr'ecalcul'ees
afin d'identifier l'extrait. L'efficacit'e de chacune de ces 'etapes
sera d'emontr'ee Ã  travers diff'erents essais et compar'ee avec la
r'ef'erence en matiÃ¨re d'empreintes audio. Nous conclurons sur l'int'erÃªt
de nos travaux et les perspectives ouvertes par ceux-ci."

 }

@InProceedings{CI-Lebosse-2006,


author = {J'erome Leboss'e and Luc Brun and Pailles, Jean Claude},
title = {A Robust Audio Fingerprint Extraction Algorithm},
booktitle = {Proceedings of SPPRA'2006},
pages = {185-192},
year = 2006,
editor= {Robert Sablatnig and O. Scherze},
address = {Innsbruck(Austria)},
month = {February},
publisher = {ACTA Press},
theme= {fingerprint},
abstract= "An Audio fingerprint is a small digest of an audio file
computed from its main perceptual properties. Like human
fingerprints, Audio fingerprints allow to identify an audio
file among a set of candidates but does not allow to
retreive any other characteristics of the
files. Applications of Audio fingerprint include audio
monitoring on broadcast chanels, filtering peer to peer
networks, meta data restoration in large audio library and
the protection of author's copyrights within a Digital
Right Management(DRM) system. We propose in this paper a
new fingerprint extraction algorithm which combines a
segmentation method with a new fingerprint construction
scheme. The proposed method is robust against compression
and time shifting alterations of the audio files.",
url ={article(ps):=https://brunl01.users.greyc.fr/ARTICLES/sppra2006.ps}

 }

@INPROCEEDINGS{CI-Dupe2009a,


author = {Dup'e, F. -X. and Brun, L.},
title = {Edition within a graph kernel framework for shape recognition},
booktitle = {Graph Based Representation in Pattern Recognition 2009},
year = {2009},
theme={shape,pattern},
pages = {11-21},
url={paper(pdf):=https://brunl01.users.greyc.fr/ARTICLES/gbr2009_dupe.pdf},
abstract={ The medial axis being an homotopic transformation, the
skeleton of a 2D shape corresponds to a planar graph having one face
for each hole of the shape and one node for each junction or
extremity of the branches. This graph is non simple since it can be
composed of loops and multiple-edges. Within the shape comparison
framework, such a graph is usually transformed into a simpler
structure such as a tree or a simple graph hereby loosing major
information about the shape. In this paper, we propose a graph
kernel combining a kernel between bags of trails and a kernel
between faces. The trails are defined within the original complex
graph and the kernel between trails is enforced by an edition
process. The kernel between bags of faces allows to put an emphasis
on the holes of the shapes and hence on their genre. The resulting
graph kernel is positive semi-definite on the graph domain.}

 }

@INPROCEEDINGS{CI-Dupe2009b,


author = {Dup'e, F. -X. and Brun, L.},
title = {Tree covering within a graph kernel framework for shape classification.},
booktitle = {ICIAP 2009},
year = {2009},
theme={shape,pattern},
series = {Lecture Notes in Computer Science},
volume = 5716,
publisher = {Springer},
editor = {Pasquale Foggia and Carlo Sansone and Mario Vento},
pages = {278-287},
url ={paper(pdf):=https://brunl01.users.greyc.fr/ARTICLES/ICIAP2009DupeBrun.pdf},
abstract={ The medial axis being an homotopic transformation, the
skeleton of a 2D shape corresponds to a planar graph having one face
for each hole of the shape and one node for each junction or
extremity of the branches. This graph is non simple since it can be
composed of loops and multiple-edges. Within the shape comparison
framework, such a graph is usually transformed into a simpler
structure such as a tree or a simple graph hereby loosing major
information about the shape. In this paper, we propose a graph
kernel combining a kernel between bags of trails and a kernel
between faces. The trails are defined within the original complex
graph and the kernel between trails is enforced by an edition
process. The kernel between bags of faces allows to put an emphasis
on the holes of the shapes and hence on their genre. The resulting
graph kernel is positive semi-definite on the graph domain.}

 }

@InProceedings{CI-Dupe2009c,


author = {Dup'e, F. -X. and Brun, L.},
title = {Shape classification using a flexible graph kernel},
booktitle = {Proceedings of CAIP 2009},
year = 2009,
editor = {Xiaoyi Jiang},
month = {September},
publisher = {LNCS},
theme={shape,pattern},
url={paper(pdf):=https://brunl01.users.greyc.fr/ARTICLES/caip2009.pdf},
abstract = {The medial axis being an homotopic transformation, the
skeleton of a 2D shape corresponds to a planar graph having one face
for each hole of the shape and o ne node for each junction or
extremity of the branches. This graph is non simple since it can be
composed of loops and multiple-edges. Within the shape comparison
framework, s uch a graph is usually transformed into a simpler
structure such as a tree or a simp le graph hereby loosing major
information about the shape. In this paper, we propose a graph
kernel combining a kernel between bags of trails and a kernel
between faces. T he trails are defined within the original complex
graph and the kernel between trails is enforced by an edition
process. The kernel between bags of faces allows to put an empha sis
on the holes of the shapes and hence on their genre. The resulting
graph kernel is po sitive semi-definite on the graph domain.}

 }

@inproceedings{CI-stanovic-2022,


TITLE = {{Maximal Independent Vertex Set applied to Graph Pooling}},
AUTHOR = {Stanovic, Stevan and Ga{"u}z{`e}re, Benoit and Brun, Luc},
BOOKTITLE = {{Structural and Syntactic Pattern Recognition (SSPR)}},
ADDRESS = {Montr{'e}al, Canada},
YEAR = {2022},
MONTH = Aug,
KEYWORDS = {Graph Neural Networks ; Graph Pooling ; Graph Classification ; Maximal Independant Vertex Set ; Graph Neural Networks},
url= {HAL:=https://hal.archives-ouvertes.fr/hal-03739114, pdf:= https://hal.archives-ouvertes.fr/hal-03739114/file/main.pdf, ArXiv:=https://arxiv.org/abs/2208.01648},
theme="pattern",
abstract={Convolutional neural networks (CNN) have enabled major advances in image classification through convolution and pooling. In particular, image pooling transforms a connected discrete grid into a reduced grid with the same connectivity and allows reduction functions to take into account all the pixels of an image. However, a pooling satisfying such properties does not exist for graphs. Indeed, some methods are based on a vertex selection step which induces an important loss of information. Other methods learn a fuzzy clustering of vertex sets which induces almost complete reduced graphs. We propose to overcome both problems using a new pooling method, named MIVSPool. This method is based on a selection of vertices called surviving vertices using a Maximal Independent Vertex Set (MIVS) and an assignment of the remaining vertices to the survivors. Consequently, our method does not discard any vertex information nor artificially increase the density of the graph. Experimental results show an increase in accuracy for graph classification on various standard datasets.}
}@inproceedings{CI-GOFFE-2011,
author = {Romain {Goffe} and Luc {Brun} and Guillaume {Damiand}},
title = {Tiled top down pyramids and segmentation of large
histological images},
booktitle = {In 8th IAPR - TC-15 Workshop on Graph-based
Representations in Pattern Recognition (GBR'11)},
publisher = {Springer},
editor = {Xiaoyi {Jiang} and Miquel {Ferrer} and Andrea {Torsello}},
series = {Lecture Notes in Computer Science},
volume = {6658},
pages = {255-264},
year = {2011},
month = {May},
url = {HAL:= http://hal.archives-ouvertes.fr/hal-00596703, pdf:=http://hal.archives-ouvertes.fr/docs/00/59/67/03/PDF/GoffeAl11-GBR.pdf,poster(pdf):=http://hal.archives-ouvertes.fr/docs/00/59/67/03/ANNEX/GoffeAl11-GBR-poster_1_.pdf},
keywords = {Irregular pyramid; Topological model; Combinatorial map;},
abstract = {
Recent microscopic imaging systems such as whole slide scanners
provide very large (up to 18GB) high resolution images. Such amounts
of memory raise major issues that prevent usual image representation
models from being used. Moreover, using such high resolution images,
global image features, such as tissues, does not clearly appear at
full resolution. Such images contain thus different hierarchical
information at different resolutions. This paper presents the model
of tiled top-down pyramids which provides a framework to handle such
images. This model encodes a hierarchy of partitions of large images
defined at different resolutions. We also propose a generic
construction scheme of such pyramids whose validity is evaluated on
an histological image application.
},
theme = {hierarchical}

 }

@InBook{brun-2012,


author = {Luc Brun and Walter Kropatsch},
title = {Image Processing and Analysing With Graphs: Theory and Practice},
chapter = {Hierarchical Graph Encoding},
publisher = {CRC Press},
year = 2012,
theme = {hierarchical},
url = {pdf:=https://www.researchgate.net/publication/229476153_Image_Processing_and_Analysing_With_Graphs_Theory_and_Practice}

 }

@INPROCEEDINGS{CI-FOUREY-2009,


author = {Fourey, S'ebastien and Brun, Luc},
title = {A first step toward combinatorial pyramids in {n-D} spaces},
booktitle = {Graph-based Representations in Pattern Recognition},
year = 2009,
volume = 5534,
series = {Lecture Notes in Computer Sciences},
pages = {304--313},
address = {Venice, Italy},
month = {May},
publisher = {Springer},
theme = {hierarchical},
url = {paper(pdf) :=https://brunl01.users.greyc.fr/ARTICLES/GbR2009FoureyBrun.pdf},
abstract= "Combinatorial maps define a general framework
which allows to encode any subdivision of an $n$D
quasi-manifold orientable and with or without
boundaries. Combinatorial pyramids are defined as
stacks of successively reduced combinatorial
maps. Such pyramids provide a rich framework which
allows to encode fine properties of the encoded
objects (either shape or partitions). Combinatorial
pyramids have first been defined in 2D. This first
work has latter been extended to pyramids of $n$D
generalized combinatorial maps. Such pyramids allow
to encode stacks of non orientable partitions but at
the price of a twice bigger pyramid. Such pyramids
are also not designed to capture efficiently the
properties connected with the orientation of
orientable objects. The present work presents our
first result on the design of a $n$D pyramid of
combinatorial maps."

 }

@INPROCEEDINGS{CI-FOUREY-2009-1,


author = {Fourey, S'ebastien and Brun, Luc},
title = {Connecting walks and connecting dart sequences for {n-D} combinatorial pyramids},
booktitle = {Proceedings of the workshop on Computational Topology in Image Context},
year = 2009,
editor = {Kroptach, W. G. and Molina, H. and Ion, A.},
pages = {67--74},
address = {St. Kathrein/Offenegg, Austria},
month = {Aug.},
key = {ISBN: 978-3-200-01582-1},
theme = {hierarchical}

 }

@INPROCEEDINGS{CI-FOUREY-2009-2,


author = {Fourey, S'ebastien and Brun, Luc},
title = {Connecting walks and connecting dart sequences for {n-D} combinatorial pyramids},
booktitle = {Progress in Combinatorial Image Analysis (International Workshop on Combinatorial Image Analysis)},
year = 2009,
editor = {Wiederhold, P. and Barneva, R. P.},
pages = {109--122},
address = {Cancun, Mexico},
month = {Nov.},
publisher = {Research Publishing Services},
theme = {hierarchical},
url = {paper(pdf):=https://brunl01.users.greyc.fr/ARTICLES/iwcia2009FoureyBrun.pdf},

abstract= "Combinatorial maps define a general framework
which allows to encode any subdivision of an $n$-D
orientable quasi-manifold with or without
boundaries. Combinatorial pyramids are defined as
stacks of successively reduced combinatorial
maps. Such pyramids provide a rich framework which
allows to encode fine properties of objects (either
shapes or partitions). Combinatorial pyramids have
first been defined in 2D. This first work has later
been extended to pyramids of $n$-D generalized
combinatorial maps. Such pyramids allow to encode
stacks of non orientable partitions but at the price
of a twice bigger pyramid. These pyramids are also
not designed to capture efficiently the properties
connected with orientation. replace{The
present}{This} work presents the design of pyramids
of $n$-D combinatorial maps and important notions
for their encoding and processing."

 }

@InProceedings{CI-FOUREY-2010,


author = {Fourey, S'ebastien and Brun, Luc},
title = {Efficient encoding of {n-D} combinatorial pyramids},
booktitle = {Proceedings of the International Conference on Pattern Recognition (ICPR'2010)},
year = {2010},
address = {Istanbul, Turkey},
month = {August},
theme = {hierarchical},
url ={paper(pdf):=https://brunl01.users.greyc.fr/ARTICLES/icpr2010FoureyBrun.pdf},
abstract= "Combinatorial maps define a general framework
which allows to encode any subdivision of an $n$-D
orientable quasi-manifold with or without
boundaries. Combinatorial pyramids are defined as
stacks of successively reduced combinatorial
maps. Such pyramids provide a rich framework which
allows to encode fine properties of objects (either
shapes or partitions). Combinatorial pyramids have
first been defined in 2D, then extended using $n$-D
generalized combinatorial maps. We motivate and
present here an implicit and efficient way to encode
pyramids of $n$-D combinatorial maps."

 }

@inproceedings{CI-Goffe-2010,


author = {Romain {Goffe} and Guillaume {Damiand} and Luc {Brun}},
title = {A causal extraction scheme in top-down pyramids for
large images segmentation},
booktitle = {In 13th International Workshop On Structural and Syntactic Pattern Recognition (SSPR'10)},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
volume = {6218},
pages = {264-274},
year = {2010},
month = {August},
theme = {hierarchical},
url ={HAL:=http://hal.archives-ouvertes.fr/hal-00567656, pdf:=http://hal.archives-ouvertes.fr/docs/00/58/87/51/PDF/GoffeAl10-SSPR.pdf, poster:=http://hal.archives-ouvertes.fr/docs/00/58/87/51/ANNEX/poster.pdf}

 }

@article{RI-GOFFE-2011,


author = {Romain {Goffe} and Luc {Brun} and Guillaume {Damiand}},
title = {Tiled top down combinatorial pyramids for large images
representation},
journal = {International Journal of Imaging Systems and Technology},
volume = {21},
number = {1},
publisher = {Wiley Subscription Services, Inc., A Wiley Company},
issn = {1098-1098},
doi = {10.1002/ima.20270},
pages = {28--36},
keywords = {irregular pyramid, topological model, tiled data
structure, combinatorial map},
year = {2011},
url={Abstract and Pdf :=http://hal.archives-ouvertes.fr/hal-00567701, Wiley library :=http://dx.doi.org/10.1002/ima.20270},
theme={hierarchical}

 }

@InProceedings{CI-Goffe-2009,


author = {Romain {Goffe} and Guillaume {Damiand} and Luc {Brun}},
title = {Extraction of tiled top-down irregular pyramids from large images.},
booktitle = {13th International Workshop on Combinatorial Image
Analysis (IWCIA'09)},
series = {Research Publishing Services},
publisher = {RPS, Singapore},
pages = {123-137},
month = {November},
year = {2009},
editor = {Petra {Wiederhold} and Reneta P. {Barneva}},
theme="hierarchical",
keywords = {Irregular pyramid; Topological model; Tiled data
structure; Combinatorial map;},
url = {HAL:= http://hal.archives-ouvertes.fr/hal-00441252, pdf:=http://hal.archives-ouvertes.fr/hal-00441252, slides:=http://hal.archives-ouvertes.fr/docs/00/58/87/50/ANNEX/slides.pdf},
abstract = {Processing large images is a common issue in the
computer vision framework with applications such as
satellite or microscopic images. The major problem
comes from the size of those images that prevents
them from being loaded globally into
memory. Moreover, such images contain different
information at different levels of resolution. For
example, global features, such as the delimitation
of a tissue, appear at low resolution whereas finer
details, such as cells, can only be distinguished at
full resolution. Thus, the objective of this paper
is the definition of a suitable hierarchical data
structure that would provide full access to all the
properties of the image by representing topological
information. The idea consists in transposing the
notion of tile for top-down topological pyramids to
control accurately the amount of memory required by
the construction of our model. As a result, this
paper defines the topological model of tiled
top-down pyramid and proposes a construction scheme
that would not depend on the system memory
limitations. }

 }

@article{RI-BRUN-2009,


author = {Aline Deruyver and
Yann Hod{'e} and
Luc Brun},
title = {Image interpretation with a conceptual graph: Labeling over-segmented
images and detection of unexpected objects},
journal = {Artif. Intell.},
volume = {173},
number = {14},
year = {2009},
pages = {1245-1265},
ee = {http://dx.doi.org/10.1016/j.artint.2009.05.003},
bibsource = {DBLP, http://dblp.uni-trier.de},
theme="nonhierarchique",
abstract={The labeling of the regions of a segmented image according
to a semantic representation (ontology) is usually
associated with the notion of understanding. The
high combinatorial aspect of this problem can be
reduced with local checking of constraints between
the elements of the ontology. In the classical
definition of Finite Domain Constraint Satisfaction
Problem, it is assumed that the matching problem
between regions and labels is
bijective. Unfortunately, in image interpretation
the matching problem is often non-univocal. Indeed,
images are often over-segmented: one object is made
up of several regions. This non-univocal matching
between data and a conceptual graph was not possible
until a decisive step was accomplished by the
introduction of arc consistency with bilevel
constraint (FDCSPBC). However, this extension is
only adequate for a matching corresponding to
surjective functions. In medical image analysis, the
case of non-functional relations is often
encountered, for example, when an unexpected object
like a tumor appears. In this case, the data cannot
be mapped to the conceptual graph, with a classical
approach. In this paper we propose an extension of
the FDCSPBC to solve the constraint satisfaction
problem for non-functional relations.}

 }

@InProceedings{CI-BRUN-2008,


author = {Brun, L. and Pruvot, J.H.},
title = {Hierarchical Matching Using Combinatorial Pyramid Framework},
booktitle = {ICISP 2008},
pages = {346-355} ,
year = 2008,
volume = 5099,
address = {Cherbourg},
theme = {hierarchical},

 }

@InProceedings{CI-BRUN-2009,


author = {Romain Goffe and Guillaume Damiand and Luc Brun},
title = {A top down construction scheme for irregular pyramids},
booktitle = {V.I.S.A.P.P.'2009},
year = 2009,
series = {LNCS},
month = {February},
publisher = {Springer},
theme = {hierarchical},
note = {To be published}

 }

@InProceedings{kropatsch-00,


author = {Walter G. {K}ropatsch and Luc {B}run},
title = {Hierarchies of Combinatorial Maps},
booktitle = {CPRW'00 Proceedings},
year = 2000,
editor = {Thom{'a}s Svoboda},
address = {Persl{'a}k},
month = {February},
organization = {Czech Pattern Recognition Society} ,
abstract = "Hierarchies of graphs can be generated by
dual graph contraction. The goal is to reduce
the data structure by a constant reduction
factor while preserving certain image
properties like connectivity. Since these
graphs are typically samplings of the plane
they are by definition plane. The particular
embedding can be represented in different
ways, e.g. a pair of dual graphs relating
points and faces through boundary
segments. Combinatorial maps determine the
embedding by explicitely recording the
orientation of edges around vertices. We
summarize the formal framework which has been
set up to perform dual graph contraction with
combinatorial maps. Contraction is controlled
by kernels that can be combined in many
ways. We have shown that kernels producing a
slow reduction rate can be combined to speed
up reduction. Or, conversely, kernels
decompose into smaller kernels that generate a
more gradual reduction.",
theme = {hierarchical},
url = {article(ps):=https://brunl01.users.greyc.fr/ARTICLES/cprw00.ps}

 }

@InBook{damiand-07,


author = {Guillaume Damiand and Luc Brun},
editor = {David Coeurjolly and Annick Montanvert and Jean-Marc Chassery},
title = {G{'e}om{'e}trie discr{`e}te et images num{'e}riques},
chapter = {Cartes combinatoires pour l'analyse d'images},
publisher = {Hermes},
year = 2007,
pages = {107-124},
url = {PDF(HAL):=https://hal.science/hal-01519124/file/document-for-chapter4.pdf},
theme = {nonhierarchique}


 }

@InProceedings{yll-05,


author = {Yll Haxhimusa and Adrian Ion and Kropatsch, Walter G. and Luc Brun},
title = {Hierarchical Image Partitioning using Combinatorial Maps},
booktitle = {Joint Hungarian-Austrian Conference on Image Processing and Pattern Recognition},
pages = {179--186},
year = 2005,
editor = {D. Chetverikov and L. Czuni and M. Vincze},
address = {Hungary},
month = {May},
theme = {hierarchical}

 }

@inproceedings{ion-2005,


author={A. Ion, Y.; Haxhimusa, W. Kropatsch, L. Brun},
title={Hierarchical Image partitioning using Combinatorial Maps},
year={2005},
month={February},
address={Zell an der Pram, Austria},
booktitle={CVWW 2005},
theme = {hierarchical},
abstract ="We present a hierarchical partitioning of images
using a pairwise similarity function on a
combinatorial map based representation. We used the
idea of minimal spanning tree to find region
borders quickly and effortlessly in a bottom-up
way, based on local differences in a color
space. The result is a hierarchy of partitions with
multiple resolutions suitable for further goal
driven analysis. The algorithm can handle large
variation and gradient intensity in images. Dual
graph pyramid representations lack the explicit
encoding of edge orientation around vertices i.e
they lack an explicit encoding of the orientation
of planes, existing in combinatorial maps. Moreover
with combinatorial maps, the dual must not be
explicitly represented because one map is enough to
fully characterize the partition.",
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/cvww2005.pdf}

 }

@article{brun-06-1,


author = {Luc Brun and Walter Kropatsch},
title = {Contains and Inside relationships within combinatorial Pyramids},
journal = {Pattern Recognition},
year = 2006,
volume = 39,
number = 4,
pages = {515-526},
month = {April},
abstract= "Irregular pyramids are made of a stack of successively
reduced graphs embedded in the plane. Such pyramids are used within
the segmentation framework to encode a hierarchy of partitions. The
different graph models used within the irregular pyramid framework
encode different types of relationships between regions. This paper
compares different graph models used within the irregular pyramid
framework according to a set of relationships between regions. We
also define a new algorithm based on a pyramid of combinatorial maps
which allows to determine if one region contains the other using
only local calculus.",
theme = {hierarchical},
url={arXiv:=https://arxiv.org/abs/cs/0701150}

 }

@inproceedings{brun-00,



AUTHOR = {L. {B}run and {{K}ropatsch},Walter },
TITLE = {Irregular Pyramids with Combinatorial Maps},
BOOKTITLE = {Advances in Pattern Recognition, Joint IAPR
International Workshops SSPR'2000 and SPR'2000},
EDITOR = {{Amin}, Adnan and
{Ferri}, Francesc J. and
{Pudil}, Pavel and
{I~{n}esta}, Francesc J.},
PUBLISHER = {Springer, Berlin Heidelberg, New York},
SERIES = {Lecture Notes in Computer Science},
VOLUME = {Vol.~1451},
ADDRESS = {Alicante, Spain},
YEAR = {2000},
MONTH = {August},
PAGES = {256-265},
abstract = "This paper presents a new formalism for
irregular pyramids based on combinatorial
maps. Such pyramid consists of a stack of
successively reduced graph. Each smaller graph
is deduced from the preceding one by a set of
edges which have to be contracted or
removed. In order to perform parallel
contractions or removals, the set of edges to
be contracted or removed has to verify some
properties. Such a set of edges is called a
Decimation Parameter. A combinatorial map
encodes a planar graph thanks to two
permutations encoding the edges and their
orientation around the vertices. Combining the
useful properties of both combinatorial maps
and irregular pyramids offers a potential
alternative for representing structures at
multiple levels of abstraction.",
theme={hierarchical}

 }

@TechReport{TR-fourey-09-1,


url = {HAL:=http://hal.archives-ouvertes.fr/hal-00353932, pdf:=http://hal.archives-ouvertes.fr/hal-00353932/PDF/GREYC-TR-2009-1.pdf},
title = {{A first step toward combinatorial pyramids in nD spaces}},
author = {Fourey, S{'e}bastien and Brun, Luc},
keywords = {irregular pyramids; combinatorial maps},
language = {Anglais},
affiliation = {Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen - GREYC},
year = {2009},
theme = {hierarchical},
abstract = {Combinatorial maps define a general framework which
allows to encode any subdivision of an nD orientable
quasi-manifold with or without
boundaries. Combinatorial pyramids are defined as
stacks of successively reduced combinatorial
maps. Such pyramids provide a rich framework which
allows to encode fine properties of the objects
(either shapes or partitions). Combinatorial
pyramids have first been defined in 2D. This first
work has latter been extended to pyramids of nD
generalized combinatorial maps. Such pyramids allow
to encode stacks of non orientable partitions but at
the price of a twice bigger pyramid. These pyramids
are also not designed to capture efficiently the
properties connected with orientation. The present
work presents our first result on the design of an
nD pyramid of combinatorial maps.}

 }

@TechReport{TR-fourey-09,


url = {HAL:=http://hal.archives-ouvertes.fr/hal-00408202, pdf:=http://hal.archives-ouvertes.fr/hal-00408202/PDF/GREYC-TR-2009-2.pdf},
title = {Connecting walks and connecting dart sequences for n-D combinatorial pyramids},
author = {Fourey, S{'e}bastien and Brun, Luc},
keywords = {combinatorial maps;combinatorial pyramids;hierarchical models},
affiliation = {Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen - GREYC},
note = {GREYC-TR-2009-2 GREYC-TR-2009-2 },
year = {2009-07},
theme = {hierarchical},
abstract = {Combinatorial maps define a general framework which
allows to encode any subdivision of an n-D
orientable quasi-manifold with or without
boundaries. Combinatorial pyramids are defined as
stacks of successively reduced combinatorial
maps. Such pyramids provide a rich framework which
allows to encode fine properties of objects (either
shapes or partitions). Combinatorial pyramids have
first been defined in 2D. This first work has later
been extended to pyramids of n-D generalized
combinatorial maps. Such pyramids allow to encode
stacks of non orientable partitions but at the price
of a twice bigger pyramid. These pyramids are also
not designed to capture efficiently the properties
connected with orientation. This work presents the
design of pyramids of n-D combinatorial maps and
important notions for their encoding and
processing.}

 }

@TechReport{brun-00-1,


author = {L. {B}run and Walter {K}ropatsch},
title = {The Construction of Pyramids with Combinatorial Maps},
institution = {Institute of Computer Aided Design},
year = 2000,
number = 63,
url = {article:=ftp://www.prip.tuwien.ac.at/pub/publications/trs/tr63.ps.gz},
address = {Vienna University of Technology, lstr. 3/1832,A-1040 Vienna AUSTRIA},
month = {June},
url = {http://www.prip.tuwien.ac.at/},
abstract = " This paper presents a new formalism for irregular
pyramids based on combinatorial maps. This
technical report continues the work begun with the
TR-54 and TR-57 reports (see ~cite{brun-99-1}
and~cite{brun-99-3}).We provide in this technical
report algorithms allowing efficient parallel or
sequential implementation of combinatorial
pyramids",
theme={hierarchical}

 }

@InProceedings{brun-01,


author = {Luc {B}run and Walter {K}ropatsch},
title = {Contraction Kernels and Combinatorial Maps},
booktitle = {$3^{rd}$ IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition},
pages = {12-21},
year = 2001,
editor = {{J}olion, Jean Michel and Walter Kropatsch and Mario Vento},
address = {Ischia Italy},
month = {May},
organization = {IAPR-TC15},
publisher = {CUEN},
theme = {hierarchical},
url = {slides:=https://brunl01.users.greyc.fr/ARTICLES/slides_gbr2001_1.ppt},
abstract = "Graph pyramids are made of a stack of successively
reduced graphs embedded in the plane. Such pyramids
overcome the main limitations of their regular
ancestors. The graphs used in the pyramid may be
region adjacency graphs, dual graphs or
combinatorial maps. Compared to the usual graph data
structures, combinatorial maps offer an explicit
encoding of the orientation of edges around
vertices. Each combinatorial map in the pyramid is
generated from the one below by a set of edges to be
contracted. This contraction process is controlled
by kernels that can be combined in many ways. We
show in this paper, that kernels producing a slow
reduction rate can be combined to speed up
reduction. Or, conversely, kernels decompose into
smaller kernels that generate a more gradual
reduction. We also propose one sequential and one
parallel algorithm to compute the contracted
combinatorial maps defined by kernels."

 }

@InProceedings{brun-01-1,


author = {Luc {B}run and Myriam Mokhtari},
title = {Graph Based Representations in Different Application Domains},
booktitle = {$3^{rd}$ IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition},
pages = {115-124},
year = 2001,
theme = {topologie},
editor = {{J}olion, Jean Michel and Walter Kropatsch and Mario Vento},
address = {Ischia Italy},
month = {May},
organization = {IAPR-TC15},
publisher = {CUEN},
theme = {hierarchical},
url = {slides:=https://brunl01.users.greyc.fr/ARTICLES/slides_gbr2001_2.ppt},
abstract = " The design of a graph based application is often
dependent of the data structure used to encode the
graph. Several papers submitted to GbR'2001 face to
close problems with different graph data
structures. Some other papers use a same data
structure but different strategies to solve a
similar problem. The aim of this counter-paper is
to point out possible interactions between these
methods. To this end, we will review some graph
data structures often used in image analysis and
illustrate each data structure by some
applications.",
note = "Invited conference",

 }

@INCOLLECTION{brun-02-1,


AUTHOR = {Luc {B}run and Walter {K}ropatsch},
TITLE = {Introduction to Combinatorial Pyramids},
BOOKTITLE = {Digital and Image Geometry},
PAGES = {108-127},
PUBLISHER = {Springer Verlag},
YEAR = 2001,
EDITOR = {G. Bertrand, A. Imiya, R. Klette},
VOLUME = 2243,
SERIES = {LNCS},
abstract= "A pyramid is a stack of image representations with
decreasing resolution. Many image processing algorithms
run on this hierarchical structure in O(log(n))
parallel processing steps where n is the diameter of
the input image. Graph pyramids are made of a stack of
successively reduced graphs embedded in the plane. Such
pyramids overcome the main limitations of their regular
ancestors. The graphs used in the pyramid may be region
adjacency graphs or dual graphs. This paper reviews the
different hierarchical data structures and introduces a
new representation named combinatorial pyramid.",
url = {slides (ppt):=https://brunl01.users.greyc.fr/ARTICLES/dgi.ppt, article (pdf):=https://brunl01.users.greyc.fr/ARTICLES/dgi.pdf},
theme = {hierarchical}

 }

@INPROCEEDINGS{brun-02-2,


AUTHOR = {Luc Brun and Walter Kropatsch},
TITLE = {Receptive Fields within the Combinatorial Pyramid Framework},
BOOKTITLE = {Discrete Geometry for Computer Imagery},
PAGES = {92-101},
YEAR = 2002,
EDITOR = {Achille Braquelaire and Lachaud, Jacques-Olivier and Anne Vialard},
VOLUME = 2301,
SERIES = {LNCS},
ADDRESS = {Bordeaux},
theme = {hierarchical},
MONTH = {April},
PUBLISHER = {Springer-Verlag},
NOTE = {ISBN 3-540-43380-5, ISSN 0302-9743},
ABSTRACT = {A hierarchical structure is a stack of successively
reduced image representations. Each basic element of a
hierarchical structure is the father of a set of
elements in the level below. The transitive closure of
this father-child relationship associates to each
element of the hierarchy a set of basic elements in
the base level image representation. Such a set,
called a receptive field, defines the embedding of one
element of the hierarchy on the original image. Using
the father-child relationship, global properties of a
receptive field may be computed in $O(log(m))$
parallel processing steps where $m$ is the diameter of
the receptive field. Combinatorial pyramids are
defined as a stack of successively reduced
combinatorial maps, each combinatorial map being
defined by two permutations acting on a set of half
edges named darts. The basic element of a
combinatorial pyramid is thus the dart. This paper
defines the receptive field of each dart within a
combinatorial pyramid and studies the main properties
of these sets.},
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/dgci2002.pdf},

 }

@InProceedings{brun-02-3,


author = {Luc Brun and Walter Kropatsch},
title = {Defining regions within the Combinatorial Pyramid framework},
booktitle = {Proceedings of the Computer Vision Winter Workshop},
pages = {198-207},
year = 2002,
theme = {hierarchical},
abstract = "Irregular Pyramids are defined as a stack of
successively reduced graphs. Each vertex of a reduced graph is
associated to a set of vertices in the base level graph named its
receptive field. If the initial graph is deduced from a planar
sampling grid its reduced versions are planar and each receptive
field is a region of the initial grid. Combinatorial Pyramids are
defined as a stack of successively reduced combinatorial
maps. Combinatorial maps are based on half edges named darts and the
receptive field of a dart is a sequence of darts in the base level
combinatorial map. We present in this paper preliminary results
showing how to define regions from the receptive fields of the
darts.",
url = {article(pdf):=https://brunl01.users.greyc.fr/ARTICLES/cvww2002.pdf},
editor = {Horst Wildenauer and Walter Kropatsch},
address = {Bad Ausse Austria},
month = {February}

 }

@TechReport{brun-02-4,


author = "Luc {B}run and Walter Kropatsch",
institution ="PRIP, TU Wien",
number = "PRIP-TR-yy",
title = "Labeled Pyramids with Combinatorial Maps",
year = 2002,
theme = {hierarchical},
price = "20,-",
url = {article:=ftp://www.prip.tuwien.ac.at/pub/publications/trs/tr57.ps.gz},
abstract = " Combinatorial Pyramids are defined as a stack of
successively reduced combinatorial maps. The Pyramid
construction plan defined in TR-63~cite{brun-00-1}
allows to describe a pyramid by two functions $level$ and
$state$ defined respectively on the set of darts of the
initial combinatorial map and the set of levels of the
pyramid. These two functions encode respectively the
maximum level on which a dart survives and the type of
each reduction operation. Based on these functions any
combinatorial map of the pyramid may be build from the
base by a one pass algorithm scanning all the darts of
the initial combinatorial map~cite{brun-00-1}. In this
technical report we show that algorithms with a same
sequential and parallel complexity may be designed in
order to build all the reduced combinatorial maps of the
Pyramid."

 }

@Article{brun-02-5,


author = {Luc Brun and Myriam Mokhtari and Domenger, Jean Philippe},
title = {Incremental modifications on segmented image defined
by discrete maps},
journal = {Journal of Visual Communication and Image Representation},
pages= {251-290},
volume= 14,
year = 2003,
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/incr_mod_disc_map.ps.gz},
abstract = "The data structure used to encode an image partition is
of critical importance for most of region-based segmentation
algorithms. Usual data structures are often convenient to extract
only few parameters from the partition while inducing complex
processing to compute others. Moreverer, the split and merge
operations allowed by such data structure are often restricted. A
new model~cite{braquelaire-96} allows segmentation algorithms to
extract a wide range of parameters from a partition. In this paper
we describe the two basic primitives used by segmentation algorithms
to modify a partition: the segment insertion and segment
suppression.",
theme = {nonhierarchique}

 }

@Article{brun-02-6,


author = {Luc Brun and Walter Kropatsch},
title = {Receptive Fields within the Combinatorial Pyramid Framework},
journal = {Graphical Models},
year = 2003,
pages= {23-42},
volume= 65,
abstract = "A hierarchical structure is a stack of successively
reduced image representations. Each basic element of a hierarchical
structure is the father of a set of elements in the level below. The
transitive closure of this father-child relationship associates to
each element of the hierarchy a set of basic elements in the base
level image representation. Such a set, called a receptive field,
defines the embedding of one element on the original
image. Combinatorial pyramids are defined as a stack of successively
reduced combinatorial maps, each combinatorial map being defined by
two permutations acting on a set of half edges named darts. The
basic element of a combinatorial pyramid is thus the dart. This
paper defines the receptive field of each dart within a
combinatorial pyramid and study the main properties of these sets.",
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/recep_field.pdf},
theme = {hierarchical}

 }

@Article{brun-02-7,


author = {Luc {B}run and Walter {K}ropatsch},
title = {Contraction Kernels and Combinatorial Maps},
journal = {Pattern Recognition Letters},
volume = {24},
number = 8,
pages= {1051-1057},
year = 2003,
month = {April},
abstract= "Graph pyramids are made of a stack of successively
reduced graphs embedded in the plane. Such pyramids overcome the
main limitations of their regular ancestors. The graphs used in the
pyramid may be region adjacency graphs, dual graphs or combinatorial
maps. Compared to usual graph data structures, combinatorial maps
offer an explicit encoding of the orientation of edges around
vertices. Each combinatorial map in the pyramid is generated from
the one below by a set of edges to be contracted. This contraction
process is controlled by kernels that can be combined in many
ways. This paper shows that kernels producing a slow reduction rate
can be combined to speed up reduction. Conversely, kernels decompose
into smaller kernels that generate a more gradual reduction. We also
propose one sequential and one parallel algorithm to compute the
contracted combinatorial maps.",
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/cont_kernel_combi_maps.pdf},
theme = {hierarchical}

 }

@InProceedings{brun-96-3,


author = "L. {B}run and Domenger, J. P.",
title = "A new split and merge algorithm with Topological maps and inter-pixel Boundaries ",
booktitle = "The fifth International Conference in Central Europe
on Computer Graphics and Visualization",
year = 1997,
month = "february",
theme = {nonhierarchique},
url= {article:=https://brunl01.users.greyc.fr/ARTICLES/new_split_merge.ps.gz},
abstract = " Usually, the segmentation algorithms implementing
the split and merge operations are restricted to a
split stage followed by a merge stage. In this
paper, we present a new split and merge algorithm
combining alternatively split and merge operations
at each recursive step. This algorithm is based on
a data structure called {em discrete
map}~cite{braquelaire-96}. This data structure
provides an efficient framework to implement split
and merge operations."

 }

@PhdThesis{brun-02-9,


author = {Luc Brun},
title = {Traitement d'images couleur et pyramides combinatoires},
school = {Universit{'e} de Reims},
year = 2002,
theme = {topologie,hierarchical,couleur,quantification,inversion},
type = {Habilitation {`a} diriger des recherches},
abstract = "We describe in this thesis three key steps of image
processing algorithms. We first study the reflexion models which
describe the image formation process. These models are used to
obtain a segmentation of the image into materials and to reconstruct
the surface of some of the regions previously segmented. The
materials studded for the reconstruction stage are metallic ones.
We also study quantization and inverse colormap operations. These
operations are used to display an image onto low cost
terminals. Such processes may also be applied into the image
compression or image segmentation framework. We finally describe a
new hierarchical model based on a topological representation of an
image partition. The model named Combinatorial Pyramid is the only
hierarchical model currently developed which allows to encode all
the topological information.",
url= {pdf:=https://brunl01.users.greyc.fr/ARTICLES/hdr.pdf,ps.gz:=https://brunl01.users.greyc.fr/ARTICLES/hdr.ps.gz}

 }

@PhdThesis{brun-96-4,


author = "L. {B}run",
title = "Segmentation d'images couleur {`a} base Topologique",
school = "Universit{'e} Bordeaux I",
year = 1996,
key = 1651,
theme = {nonhierarchique},
address = "351 cours de la Lib{'e}ration 33405 Talence",
month = "December",
url = "these:=https://brunl01.users.greyc.fr/ARTICLES/these.ps.gz",
abstract = "La segmentation est un processus visant {`a}
extraire des objets pr{'e}sents dans une image. La
plupart des m{'e}thodes de segmentation
d{'e}velopp{'e}es jusqu'{`a} pr{'e}sent sont d{'e}volues
{`a} une classe d'images particuli{`e}re (photo
satellite, image IRM, etc.). De plus l'information
colorim{'e}trique contenue dans les images est
insuffisamment prise en compte. Le but de ce
travail est de rem{'e}dier {`a} ces deux
limitations. Nous proposons deux m{'e}thodes
permettant d'extraire des informations pertinentes
{`a} partir d'ensembles de couleurs. Nous proposons
de plus plusieurs m{'e}thodes de segmentation
bas{'e}es sur les cartes planaires et sur une
repr{'e}sentation des r{'e}gions par fronti{`e}res
inter-pixels. Ces m{'e}thodes sont tr{`e}s
g{'e}n{'e}rales et utilisent un environnement de
programmation permettant de d{'e}velopper rapidement
des logiciels de segmentation."

 }

@InProceedings{brun-97,


author = "L. {B}run and Bazin, J. M.",
title = "Am{'e}lioration des performances d'un syst{`e}me de
segmentation par l'utilisation d'un syst{`e}me expert",
year = 1998,
theme = {nonhierarchique},
booktitle = "Advances in Intelligent Computing- IPMU'98",
organization = "IPMU",
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/ipmu.ps.gz},
abstract = " Nous allons pr{'e}senter un nouveau syst{`e}me de
segmentation bas{'e} sur une collaboration entre un
algorithme de segmentation existant et un syst{`e}me
expert. Le nouveau syst{`e}me se distingue de
l'algorithme de segmentation pr{'e}c{'e}dent par une
distinction claire entre les connaissances de l'expert
en Imagerie et les algorithmes utilisant ces
connaissances. Le gain en modularit{'e} obtenu permet
d'enrichir facilement la base de connaissances et de
diminuer le nombre de questions triviales pos{'e}es {`a}
l'utilisateur."

 }

@InProceedings{brun-97-2,


author = "Luc {B}run and Domenger, Jean Philipe and Braquelaire, Jean Pierre",
title = "Discrete maps : a framework for region segmentation algorithms",
booktitle = "Workshop on Graph based representations",
year = 1997,
month = "April",
theme = {nonhierarchique},
OPTorganization = "IAPR-TC15",
address = "Lyon",
url= {article (.ps.gz):=https://brunl01.users.greyc.fr/ARTICLES/GbR97.ps.gz},
note = "published in Advances in Computing (Springer)",
abstract = "In this paper, we present different recent
segmentation works based on discrete maps. Discrete
maps provide an efficient framework for region based
segmentation methods. A discrete is a mixed model. It
combines an encoding of the discrete boundaries of
the image regions with topological graphs which
represents the topology of the image."

 }

@TechReport{brun-99-1,


author = {Luc {B}run and Walter Kropatsch},
title = {Dual Contractions of Combinatorial Maps},
institution = {Institute of Computer Aided Design},
year = 1999,
number = 54,
url = {article:=ftp://www.prip.tuwien.ac.at/pub/publications/trs/tr54.ps.gz},
theme = {hierarchical},
address = {Vienna University of Technology, lstr. 3/1832,A-1040 Vienna AUSTRIA},
month = {January},
url = { http://www.prip.tuwien.ac.at/},
abstract = " This paper presents a new formalism for irregular
pyramids based on combinatorial maps. The
combinatorial map formalism allows us to encode a
planar graph thanks to two permutations encoding the
edges and the vertices of the graph.The combinatorial
map formalism encode explicitly the orientation of the
planar graph. This last property is useful to describe
the partitions of an image which may be considered as
a subset of the oriented plane $IR^2$. This new
constraint allows us to design interesting properties
for irregular pyramids. Finally the combinatorial
formalism allows us to encode efficiently the graph
transformations used in irregular pyramids."

 }

@inproceedings{brun-99-2,



AUTHOR = {L. {B}run and {K}ropatsch, Walter},
TITLE = {Dual Contraction of Combinatorial Maps},
BOOKTITLE = {$2^{nd}$ IAPR-TC-15 Workshop on Graph-based Representations},
EDITOR = {{Kropatsch},Walter and
{{J}olion}, J.-M.},
PUBLISHER = {{"O}sterreichische Computer Gesellschaft},
VOLUME = {126},
ADDRESS = {Haindorf, Austria},
YEAR = {1999},
MONTH = {May},
PAGES = {145-154},
theme = {hierarchical},
url = {slides:=https://brunl01.users.greyc.fr/ARTICLES/slides_cvww1999.ps},
abstract = "This paper presents a new formalism for
irregular graph pyramids based on
combinatorial maps. Such pyramids consist of
a stack of successively reduced graphs. Each
smaller graph is derived from the larger one
in the stack by a graph transformation called
dual graph contraction. The basic operations
of this transformation are contraction and
removal of edges. In this paper these two
basic operations are translated into the
formalism of combinatorial maps and should
enable the construction of combinatorial
pyramids. A combinatorial map encodes a
planar graph by two permutations encoding the
edges and their orientation around the
vertices. Combining the useful properties of
irregular pyramids offers a potential
alternative for representing structures at
multiple levels of abstraction."

 }

@TechReport{brun-99-3,


author = "Luc {B}run and Walter Kropatsch",
institution ="PRIP, TU Wien",
number = "PRIP-TR-057",
title = "Pyramids with Combinatorial Maps",
year = 1999,
price = "20,-",
theme = {hierarchical},
url = {article:=ftp://www.prip.tuwien.ac.at/pub/publications/trs/tr57.ps.gz},
abstract = "This paper presents a new formalism for irregular pyramids
based on combinatorial maps. This technical report continue the work
began with the TR-54 report. Definition and
properties of Contraction kernels are generalized and completed. The
definition and properties of Equivalent contraction kernels are also
given. ",

 }

@InProceedings{brun-99-4,


author = {L. {B}run},
title = {Mod{`e}les Math{'e}matiques et Repr{'e}sentation discr{`e}tes pour la Description des Images Couleurs},
booktitle = {{'E}cole d'{'e}t{'e} - Images Couleur},
year = 1999,
address = {Site GIAT Industries, Saint Etienne},
month = {September},
theme = {nonhierarchique,couleur},
url = {slides(ppt):=https://brunl01.users.greyc.fr/ARTICLES/presentation_ecole_ete.ppt, article(.ps.gz):=https://brunl01.users.greyc.fr/ARTICLES/ecole_ete.ps.gz},
abstract = "Nous allons pr{'e}senter dans ce document, un
syst{`e}me permettant {`a} l'utilisateur de guider le
processus de segmentation. La prise en compte des
interventions de l'utilisateur et les modifications de
la partition en fonction de celles-ci sont
r{'e}alis{'e}es {`a} l'aide d'un mod{`e}le permettant de
coder la g{'e}om{'e}trie et la topologie d'une
partition. Ce mod{`e}le, combin{'e} {`a} plusieurs
algorithmes de segmentation ainsi qu'a diverses
fonctions d'{'e}ditions, permet {`a} l'utilisateur de
d{'e}signer interactivement les r{'e}gions qui doivent
{^e}tre d{'e}coup{'e}es ou fusionn{'e}es. Cette
interaction entre l'utilisateur et les algorithmes de
segmentation doit permettre d'obtenir de bons
r{'e}sultats sur une tr{`e}s grande vari{'e}t{'e} d'images
sans ajustement de param{`e}tres."

 }

@InProceedings{brun-03,


author = {Luc Brun and Walter Kropatsch},
title = {Implicit encoding of combinatorial Pyramids},
booktitle = {Proceedings of the Computer Vision Winter Workshop},
pages = {49-54},
year = 2003,
editor = {Ondrej Drbohlav},
address = {Valtice, Czech Reublic},
month = {February},
url = { article:=https://brunl01.users.greyc.fr/ARTICLES/cvww2003.pdf},
abstract = " An irregular pyramid consists of a stack of
successively reduced graphs. Each smaller graph is deduced from the
preceding one by the contraction or the removal of a set of
edges. Using a fixed decimation ratio we need approximately
O(log(image size)) graphs to encode the whole
pyramid. A combinatorial map encodes a planar graph thanks to two
permutations encoding the edges and their orientation around the
vertices. We present in this article an encoding of a combinatorial
pyramid which allows to fold the whole pyramid in the base level
layer and provides at the same time a measure of the importance of
every pixel. Any reduced combinatorial maps of the pyramid maybe
directly retrieved from this encoding if needed.",
theme = {hierarchical}

 }

@InProceedings{brun-03-1,


author = {Luc Brun and Walter Kropatsch},
title = {Combinatorial Pyramids},
booktitle = {IEEE International conference on Image Processing (ICIP)},
pages = {33-37},
year = 2003,
editor = {Suvisoft},
volume = {II},
address = {Barcelona},
month = {September},
organization = {IEEE},
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/icip2003.pdf, slides:=https://brunl01.users.greyc.fr/ARTICLES/slides_icip2003.pdf},
abstract = "An irregular pyramid consists of a stack of successively
reduced graphs. Each smaller graph is deduced from the preceding one
by the contraction or the removal of a set of edges. Using a fixed
decimation ratio we need approximately O(log(image size)) graphs to
encode the whole pyramid. A combinatorial map encodes a planar graph
thanks to two permutations encoding the edges and their orientation
around the vertices. We present in this article an encoding of a
combinatorial pyramid which allows to fold the whole pyramid in the
base level layer and provides at the same time a measure of the
relevance of every pixel. This encoding is used to retreive any
reduced combinatorial map of the pyramid from its base and to
compute the borders of the partition encoded by the combinatorial
maps.",
theme = {hierarchical}

 }

@InProceedings{brun-03-2,


author = {Luc Brun and Walter Kropatsch},
title = {Construction of Combinatorial Pyramids},
booktitle = {Graph based Representations in Pattern Recognition},
pages = {1-12},
year = 2003,
editor = {Edwin Hancock and Mario Vento},
volume = 2726,
series = {LNCS},
address = {York, UK},
month = {June},
organization = {IAPR-TC15},
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/gbr2003.pdf,slides:=https://brunl01.users.greyc.fr/ARTICLES/slides_gbr2003.pdf},
abstract = "Irregular pyramids are made of a stack of successively
reduced graphs embedded in the plane. Each vertex of a reduced graph
corresponds to a connected set of vertices in the level below. One
connected set of vertices reduced into a single vertex at the above
level is called the reduction window of this vertex. In the same
way, a connected set of vertices in the base level graph reduced to
a single vertex at a given level is called the receptive field of
this vertex. The graphs used in the pyramid may be region adjacency
graphs, dual graphs or combinatorial maps. This last type of
pyramids are called Combinatorial Pyramids. Compared to usual graph
data structures, combinatorial maps encode one graph and its dual
within a same formalism and offer an explicit encoding of the
orientation of edges around vertices. This paper describes the
construction scheme of a Combinatorial Pyramid. We also provide a
constructive definition of the notions of reduction windows and
receptive fields within the Combinatorial Pyramid framework.",
theme = {hierarchical}

 }

@INPROCEEDINGS{barchadier-04,


AUTHOR = {Marchadier, Jocelyn and {B}run, Luc and {{K}ropatsch}, Walter G.},
TITLE = {Rooted kernels and Labeled Combinatorial Pyramids},
BOOKTITLE = {Computer Vision - CVWW'04, Proceedings of the Computer Vision Winter Workshop},
EDITOR = {{Leonardis}, Ale{v s} and {Solina}, Franc (eds.)},
PUBLISHER = {IEEE Slovenia Section},
ADDRESS = {Ljubljana},
YEAR = {2004},
theme = {hierarchical},
abstract = "An irregular pyramid consists of a stack of
successively reduced graphs. Each smaller graph is deduced
from the preceding one using contraction or removal kernels. A
contraction (resp. removal) kernel defines a forest of the
initial (resp. dual ) graph, each tree of this forest being
reduced to a single vertex (resp. dual vertex) in the reduced
graph. A combinatorial map encodes a planar graph thanks to
two permutations encoding the edges and their orientation
around the vertices. We present in this article a new
definition of contraction and removal kernels which allows to
encode the different values attached to a given vertex, dual
vertex or edge along the pyramid.",
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/cvww2004.pdf},

 }

@Article{braquelaire-96-1,


author = "Braquelaire, Jean Pierre and Brun, Luc",
title = "Image Segmentation with Topological Maps
and Inter-pixel Representation",
journal = "Journal of Visual Communication and
Image representation",
year = 1998,
volume = 9,
number = 1,
pages = {62-79},
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/seg_with_topo_map.ps.gz},
theme = {nonhierarchique},
abstract = "In this paper we present a data structure improving
region segmentation of 2D images. This data
structure provides an efficient access to both
geometric features such as the set of pixels of a
region and topological features like the frontier of
a region, the neighbors of a region or the set of
regions included in one region. It allows us to
combine different segmentation algorithms without
restriction. Interactive refinement or merge of
regions can also be performed efficiently."

 }

@InProceedings{braquelaire-96-2,


author = "Braquelaire, Jean Pierre and Luc Brun and Anne Vialard",
title = "Inter-Pixel Euclidean Paths for Image Analysis",
volume = 1176,
pages = "193-204",
booktitle = "Lecture Notes in Computer Science",
year = 1996,
organization = "Discrete Geometry for Computer Imagery",
publisher = "Springer-Verlag",
theme = {nonhierarchique},
url = {article (.ps.gz):=https://brunl01.users.greyc.fr/ARTICLES/dgci.ps.gz},
abstract = "Inter-pixel boundaries provide a robust and
consistent description of segmented images but have a
poor visual aspect, especially when being
enlarged. Approximation curve are sometimes used to
smooth discrete boundaries but they do not provide
error free reconstruction and may be uneasy to use in
this context. In this paper we show the advantages
of using Euclidean paths in order to smooth
inter-pixel boundaries and we demonstrate the
interest of inter-pixel Euclidean paths for the
purpose of image segmentation and analysis."

 }

@InProceedings{brun-04,


author = {Luc Brun and Philippe Vautrot and Fernand Meyer},
title = {Hierarchical Watersheds with Inter-pixel Boundaries},
booktitle = { Image Analysis and Recognition: International Conference ICIAR 2004, Part I},
year = 2004,
pages= {840-847},
address = {Proto (Portugal)},
publisher = {Springer Verlag Heidelberg (LNCS)},
theme = {hierarchical},
abstract = "Watersheds are the latest segmentation tool developed in
mathematical morphology. These algorithms produce a segmentation of
an image into a set of basins separated by watershed pixels. The
over segmentation produced by these algorithms is reduced by
removing all contours with a low saliency. This contour's saliency
is generally defined from the minimal height of the watershed pixels
along the contour. However, such a definition does not allow to
define a contour's saliency in case of thick watersheds. Moreover,
the set of basins which corresponds to the intuitive notion of
regions does not define an image partition. In this paper we propose
a method which allows to aggregate the watershed pixels to the
basins while preserving the notion of contour and the associated
saliency. The model used to encode the image partition is then
decimated according to the contour saliency to obtain a hierarchy of
partitions.",
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/iciar2004.pdf}

 }

@InProceedings{brun-05,


author = {Luc Brun and Myriam Mokhtari and Fernand Meyer},
title = {Hierarchical watersheds within the Combinatorial Pyramid framework},
booktitle = {Proc. of DGCI 2005},
year = 2005,
organization = {IAPR-TC18},
publisher = {LNCS},
theme = {hierarchical},
url = {article:=https://brunl01.users.greyc.fr/ARTICLES/dgci2005.ps, slides:=https://brunl01.users.greyc.fr/ARTICLES/slides_dgci2005.pdf},
abstract= "Watershed is the latest tool used in mathematical
morphology. The algorithms which implement the
watershed transform generally produce an over
segmentation which includes the right image's
boundaries. Based on this last assumption, the
segmentation problem turns out to be equivalent to
a proper valuation of the saliency of each
contour. Using such a measure, hierarchical
watershed algorithms use the edge's saliency
conjointly with statistical tests to decimate the
initial partition. On the other hand, Irregular
Pyramids encode a stack of successively reduced
partitions. Combinatorial Pyramids consitute the
latest model of this family. Within this framework,
each partition is encoded by a combinatorial map
which encodes all topological relationships between
regions such as multiple boundaries and inclusion
relationships. Moreover, the combinatorial pyramid
framework provides a direct access to the embedding
of the image's boundaries. We present in this paper
a hierarchical watershed algorithm based on
combinatorial pyramids. Our method overcomes the
problems connected to the presence of noise both
within the basins and along the watershed
contours."

 }

@InProceedings{brun-05-2,


author = {Luc Brun and Walter Kropatsch},
title = {Inside and Outside within Combinatorial Pyramids},
booktitle = {5th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition},
year = 2005,
editor = {Luc Brun and Mario Vento},
series = {Lecture Notes in Computer Science},
address = {Poitiers (France)},
month = {April},
organization = {IAPR-TC15},
publisher = {Springer, Berlin Heidelberg, New York},
theme= {hierarchical},
note = {ISBN: 3-540-25270-3},
url= {springerLink:=http://www.springerlink.com/index/V6UYD78EF8CLHQQ2},
abstract= "Irregular pyramids are made of a stack of
successively reduced graphs embedded in the
plane. Such pyramids are often used within the
segmentation and the connected component analysis
frameworks to detect meaningful objects together
with their spatial and topological
relationships. The graphs reduced in the pyramid
may be region adjacency graphs, dual graphs or
combinatorial maps. Using any of these graphs each
vertex of a reduced graph encodes a region of the
image. Using simple graphs one edge between two
vertices encodes the existence of a common boundary
between two regions. Using dual graphs and
combinatorial maps, each connected boundary segment
between two regions is associated to one
edge. Moreover, special edges called loops may be
used to differentiate a special type of adjacency
where one region surrounds the other. We show in
this article that the loop information does not
allow to distinguish inside and outside of the loop
by local computations. We provide a method based on
the combinatorial pyramid framework which uses the
orientation explicitly encoded by combinatorial
maps to determine inside and outside with local
calculus."


 }

@InProceedings{CI-ELHASSANI-2006,


author = {M. Elhassani and D. Rivasseau and M. Duranton and S. Jehan-Besson and D. Tschumperle and L. Brun and M. Revenu },
title = {Vectorization of a statistical segmentation},
booktitle = {International Congress of Imaging Science},
year = 2006,
address = {Rochester, NY, USA},
month = {May},
theme= {nonhierarchique}

 }

@InProceedings{CI-Pruvot-2007,


author = {Pruvot, Jean Hugues and Luc Brun},
title = {Hierarchy construction schemes Within the scale set framework},
booktitle = {Graph based Representation in Pattern Recognition'2007},
pages = {126-137},
year = 2007,
editor = {Francisco Escolano and Mario Vento},
number = 4538,
address = {Alicante},
month = {June},
organization = {IAPR TC15},
publisher = {LNCS},
abstract= "Segmentation algorithms based on an energy minimisation framework
often depend on a scale parameter which balances a fit to data and a
regularising term. Irregular pyramids are defined as a stack of
graphs successively reduced. Within this framework, the scale is
often defined implicitly as the height in the pyramid. However,
each level of an irregular pyramid can not usually be readily
associated to the global optimum of an energy or a global criterion
on the base level graph. This last drawback is addressed by the
scale set framework designed by Guigues. The methods designed by
this author allow to build a hierarchy and to design cuts within
this hierarchy which globally minimise an energy. This paper
studies the influence of the construction scheme of the initial
hierarchy on the resulting optimal cuts. We propose one sequential
and one parallel method with two variations within both. Our
sequential methods provide partitions near the global optima while
parallel methods require less execution times than the sequential
method of Guigues even on sequential machines.",
url="article(ps):=https://brunl01.users.greyc.fr/ARTICLES/gbr2007.ps, arXiV:=https://arxiv.org/abs/0712.1878, slides(pdf):=https://brunl01.users.greyc.fr/ARTICLES/slides_gbr2007.pdf, video:=http://videolectures.net/gbr07_pruvot_hcs/",
theme = {hierarchical},

 }

@InProceedings{CI-Hassani-06-1,


author = {El-hassani, M. and D. Rivasseau and S. Jehan-Besson and M. Revenu and D. Tschumperl{'e} and L. Brun and M. Duranton},
title = {A time-consistent video segmentation algorithm designed for real-time implementation},
booktitle = {IEEE International Conference on Electronics, Circuits and Systems},
year = 2006,
address = {Nice France},
month = {December},
theme = {nonhierarchique}

 }

@InProceedings{CI-Hassani-2006-2,


author = {El-hassani, M. and D. Rivasseau and M. Duranton and S. Jehan-Besson and D. Tschumperl{'e} and L. Brun and M. Revenu},
title = {Vectorization of a statistical segmentation},
booktitle = {International Congress of Imaging Science},
year = 2006,
address = {Rochester},
month = {May},
theme = {nonhierarchique}

 }

@InProceedings{CI-braure-2006,


author = {Braure de Calignon, M. and Luc Brun and Lachaud, Jacques Olivier},
title = {Combinatorial Pyramids and discrete geometry for energy minimizing segmentation},
booktitle = {Proc. Int. Symposium on visual Computing},
year = 2006,
number = 4292,
series = {LNCS},
address = {Lake Tahoe, Nevada},
month = {November},
publisher = {springer},
theme= {nonhierarchique},
url = {pdf:=https://brunl01.users.greyc.fr/ARTICLES/isvc2006.pdf, arXiv:=https://arxiv.org/abs/0906.2770},
abstract = "The scale set theory allows to define a hierarchy of
segmentations according to a scale parameter. This
theory closely related to the Bayesian and the Minimum
description Length(MDL) frameworks describes the
energy of a partition as the sum of two terms : a
goodness to fit and a regularisation term. This last
term may be interpreted as the encoding cost of the
model associated to the partition. It usually includes
the total length of the partition's boundaries and is
simply computed as the number of lignels between the
regions of the partition. We propose to use a better
estimation of the total length of the boundaries by
using discrete length estimators. We state the basic
properties which must be fulfilled by these estimators
and show their influence on the partitition's energy."

 }

@InProceedings{CN-Hassani-2006,


author = {M. Elhassani and D. Rivasseau and S. Jehan-Besson and M. Revenu and D. Tschumperle and L. Brun and M. Duranton},
title = {Conception d'un algorithme robuste de segmentation vid{'e}o pour des applications temps r{'e}el},
booktitle = {CORESA},
year = 2006,
address = {Caen},
month = {December},
theme = {nonhierarchique}

 }

@Article{RI-ELHASSANI-2008,


author = {Elhassani, M. and Jehan-Besson, S. and Brun, L. and Revenu, M. and Duranton, M. and Tschumperl{'e}, D. and Rivasseau, D.},
title = {A Time-Consistent Video Segmentation Algorithm designed for Real-Time Implementation},
journal ={VLSI Design},
year = {2008},
volume ={2008},
number = {Article ID 892370},
pages = {12 pages},
theme = {nonhierarchique}

 }

@InProceedings{CN-Brun-2006,


author = {Luc Brun},
title = {Segmentation, Graphes et structures hi{'e}rarchiques},
booktitle = {ORASIS 2007},
year = 2007,
address = {Obernai, France},
month = {June},
theme = {hierarchical},
url = {slide(pdf):=https://brunl01.users.greyc.fr/ARTICLES/orasis2007.pdf}

 }

@PhdThesis{TH-PRUVOT-2008,


author = {Jean Hugues Pruvot},
title = {Segmentation et appariement hiÃ©rarchiques basÃ©s sur les pyramides combinatoires },
school = {UniversitÃ© de Caen Basse Normandie - ED SIMEM },
year = 2008,
address= {France},
theme = {hierarchical},
url = {Phd:=https://brunl01.users.greyc.fr/ARTICLES/pruvotPhd.pdf}

 }

@InProceedings{CI-NEE-2008,


author = "N{'e}e, G. and Jehan-Besson, S. and Brun, L. and Revenu, M.",
title = "Significance tests and statistical inequalities for region matching",
booktitle = "Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR International Workshops S+SSPR 2008",
year = "2008",
editor = "N. da Vitaro Lobo et al.",
volume = "5342",
series = "Lecture Notes in Computer Science",
pages = "350--360",
month = "December",
publisher = "Springer",
theme = {nonhierarchique}

 }