Publications de Xavier Descombes

Résultat de la recherche dans la liste des publications :

• 44 Articles
• 1 Thèse de Doctorat et Habilitation
• 97 Articles de conférence
• 36 Rapports de recherche et Rapports techniques
• 7 Articles de collection ou Chapitres de livres
• 2 Livres

nouvelle recherche | bibtex

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44 Articles

41 - A Markov Pixon Information approach for low level image description. X. Descombes et F. Kruggel. IEEE Trans. Pattern Analysis ans Machine Intelligence, 21(6): pages 482-494, juin 1999. @ARTICLE{xd99b, author = {Descombes, X. and Kruggel, F.}, title = {A Markov Pixon Information approach for low level image description}, year = {1999}, month = {juin}, journal = {IEEE Trans. Pattern Analysis ans Machine Intelligence}, volume = {21}, number = {6}, pages = {482-494}, pdf = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=771311}, keyword = {} }

42 - GMRF Parameter Estimation in a non-stationary Framework by a Renormalization Technique: Application to Remote Sensing Imaging. X. Descombes et M. Sigelle et F. Prêteux. IEEE Trans. Image Processing, 8(4): pages 490-503, 1999. @ARTICLE{xd99a, author = {Descombes, X. and Sigelle, M. and Prêteux, F.}, title = {GMRF Parameter Estimation in a non-stationary Framework by a Renormalization Technique: Application to Remote Sensing Imaging}, year = {1999}, journal = {IEEE Trans. Image Processing}, volume = {8}, number = {4}, pages = {490-503}, url = {https://hal.archives-ouvertes.fr/hal-00272393}, keyword = {} }

43 - fMRI Signal Restoration Using an Edge Preserving Spatio-temporal Markov Random Field. X. Descombes et F. Kruggel et Y. von Cramon. NeuroImage, 8: pages 340-349, 1998. Mots-clés : fMRI, Restauration, Champs de Markov. Copyright : published in NeuroIMage by Elsevier ||http://www.elsevier.com/wps/find/homepage.cws_home @ARTICLE{descombes98d, author = {Descombes, X. and Kruggel, F. and von Cramon, Y.}, title = {fMRI Signal Restoration Using an Edge Preserving Spatio-temporal Markov Random Field}, year = {1998}, journal = {NeuroImage}, volume = {8}, pages = {340-349}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/1998_descombes98d.pdf}, keyword = {fMRI, Restauration, Champs de Markov} }

44 - Spatio-temporal fMRI analysis using Markov Random Fields. X. Descombes et F. Kruggel et Y. Von Cramon. IEEE Trans. Medical Imaging, 17(6): pages 1028-1039, 1998. Note : à paraître. Mots-clés : fMRI, Markov Random Fields. @ARTICLE{descombes98, author = {Descombes, X. and Kruggel, F. and Von Cramon, Y.}, title = {Spatio-temporal fMRI analysis using Markov Random Fields}, year = {1998}, journal = {IEEE Trans. Medical Imaging}, volume = {17}, number = {6}, pages = {1028-1039}, pdf = {http://www-sop.inria.fr/members/Xavier.Descombes/publis_dr/TMI1.pdf}, keyword = {fMRI, Markov Random Fields} }

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Thèse de Doctorat et Habilitation

1 - Méthodes stochastiques en analyse d'image : des champs de Markov aux processus ponctuels marqués. X. Descombes. Habilitation à diriger des Recherches, Universite de Nice Sophia Antipolis, février 2004. Mots-clés : Champs de Markov, Geometrie stochastique. @PHDTHESIS{Xdescombes, author = {Descombes, X.}, title = {Méthodes stochastiques en analyse d'image : des champs de Markov aux processus ponctuels marqués}, year = {2004}, month = {février}, school = {Universite de Nice Sophia Antipolis}, type = {Habilitation à diriger des Recherches}, url = {https://hal.inria.fr/tel-00506084}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/HDRdescombes.pdf}, keyword = {Champs de Markov, Geometrie stochastique} }

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97 Articles de conférence

1 - Tree crown detection in high resolution optical images during the early growth stages of eucalyptus plantations in Brazil. J. Zhou et C. Proisy et X. Descombes et J. Zerubia et G. Le Maire et Y. Nouvellon et P. Couteron. Dans Asian Conference on Pattern Recognition (ACPR), Beijing, China, novembre 2011. Mots-clés : tree detection, Eucalyptus plantation, Marked point process, multi-date detection. @INPROCEEDINGS{Zhou11, author = {Zhou, J. and Proisy, C. and Descombes, X. and Zerubia, J. and Le Maire, G. and Nouvellon, Y. and Couteron, P.}, title = {Tree crown detection in high resolution optical images during the early growth stages of eucalyptus plantations in Brazil}, year = {2011}, month = {novembre}, booktitle = {Asian Conference on Pattern Recognition (ACPR)}, address = {Beijing, China}, url = {http://hal.inria.fr/hal-00740973}, keyword = {tree detection, Eucalyptus plantation, Marked point process, multi-date detection} } Abstract : Individual tree detection methods are more and more present, and improve, in forestry and silviculture domains with the increasing availability of satellite metric imagery. Automatic detection on these very high spatial resolution images aims to determine the tree positions and crown sizes. In this paper, we used a mathematical model based on marked point processes, which showed advantages w.r.t. several individual tree detection algorithms for plantations, to analyze the eucalyptus plantations in Brazil, with 2 optical images acquired by the WorldView-2 satellite. A tentative detection simultaneously with 2 images of different dates (multi-date) was tested for the first time, which estimates individual tree crown variation during these dates. The relevance of detection was discussed considering the detection performance in tree localizations and crown sizes. Then, tree crown growth was deduced from detection results and compared with the expected dynamics of corresponding populations.

2 - Estimation of an optimal spectral band combination to evaluate skin disease treatment efficacy using multi-spectral images. S. Prigent et D. Zugaj et X. Descombes et P. Martel et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Brussels, Belgium, septembre 2011. @INPROCEEDINGS{prigent11a, author = {Prigent, S. and Zugaj, D. and Descombes, X. and Martel, P. and Zerubia, J.}, title = {Estimation of an optimal spectral band combination to evaluate skin disease treatment efficacy using multi-spectral images}, year = {2011}, month = {septembre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Brussels, Belgium}, pdf = {http://hal.inria.fr/docs/00/59/06/94/PDF/icip_final.pdf}, keyword = {} } Abstract : Clinical evaluation of skin treatments consists of two steps. First, the degree of the disease is measured clinically on a group of patients by dermatologists. Then, a statistical test is used on obtained set of measures to determine the treatment efficacy. In this paper, a method is proposed to automatically measure the severity of skin hyperpigmentation. After a classification step, an objective function is designed in order to obtain an optimal linear combination of bands defining the severity criterion. Then a hypothesis test is deployed on this combination to quantify treatment efficacy.

3 - A fast multiple birth and cut algorithm using belief propagation. A. Gamal Eldin et X. Descombes et Charpiat G. et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Brussels, Belgium, septembre 2011. Mots-clés : Multiple Birth and Cut, multiple object extraction, Graph Cut, Belief Propagation. @INPROCEEDINGS{MBC_ICIP11, author = {Gamal Eldin, A. and Descombes, X. and G., Charpiat and Zerubia, J.}, title = {A fast multiple birth and cut algorithm using belief propagation}, year = {2011}, month = {septembre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Brussels, Belgium}, url = {http://hal.inria.fr/inria-00592446/fr/}, keyword = {Multiple Birth and Cut, multiple object extraction, Graph Cut, Belief Propagation} } Abstract : In this paper, we present a faster version of the newly proposed Multiple Birth and Cut (MBC) algorithm. MBC is an optimization method applied to the energy minimization of an object based model, defined by a marked point process. We show that, by proposing good candidates in the birth step of this algorithm, the speed of convergence is increased. The algorithm starts by generating a dense configuration in a special organization, the best candidates are selected using the belief propagation algorithm. Next, this candidate configuration is combined with the current configuration using binary graph cuts as presented in the original version of the MBC algorithm. We tested the performance of our algorithm on the particular problem of counting flamingos in a colony, and show that it is much faster with the modified birth step.

4 - Extraction et caractérisation de régions saines et pathologiques à partir de micro-tomographie RX du système vasculaire cérébral. X. Descombes et A. Gamal Eldin et F. Plouraboue et C. Fonta et S. Serduc et G. Le Duc et T. Weitkamp. Dans Proc. GRETSI Symposium on Signal and Image Processing, Bordeaux, France, septembre 2011. @INPROCEEDINGS{XavierGRETSI11, author = {Descombes, X. and Gamal Eldin, A. and Plouraboue, F. and Fonta, C. and Serduc, S. and Le Duc, G. and Weitkamp, T.}, title = {Extraction et caractérisation de régions saines et pathologiques à partir de micro-tomographie RX du système vasculaire cérébral}, year = {2011}, month = {septembre}, booktitle = {Proc. GRETSI Symposium on Signal and Image Processing}, address = {Bordeaux, France}, url = {http://hal.inria.fr/inria-00625525/fr/}, keyword = {} } Abstract : In this paper, we consider X-ray micro-tomography representing the brain vascular network. We define the local vascular territories as the regions obtained after a watershed algorithm applied on the distance map. The obtained graph is then regularized by a Markov random field approach. The optimization is performed using a graph cut algorithm. We show that the resulting segmentation exhibits three classes corresponding to normal tissue, tumour and an intermediate region.

5 - Reconstruction 3D du bâti à partir d'une seule image par naissances et morts multiples. J.D. Durou et X. Descombes et P. Lukashevish et A. Kraushonak. Dans Proc. GRETSI Symposium on Signal and Image Processing, Bordeaux, France, septembre 2011. @INPROCEEDINGS{DurouGretsi11, author = {Durou, J.D. and Descombes, X. and Lukashevish, P. and Kraushonak, A.}, title = {Reconstruction 3D du bâti à partir d'une seule image par naissances et morts multiples}, year = {2011}, month = {septembre}, booktitle = {Proc. GRETSI Symposium on Signal and Image Processing}, address = {Bordeaux, France}, url = {http://hal.inria.fr/inria-00625527/fr/}, keyword = {} } Résumé : Dans cet article, nous nous écartons de l’approche classique qui considère la reconstruction 3D comme un problème inverse et la résout en mettant en correspondance deux images d’une paire stéréoscopique. Au contraire, nous montrons qu’il est plus simple de résoudre le problème direct. Pour ce faire, nous proposons aléatoirement des configurations de bâtiments pour ne conserver que les plus pertinentes par un algorithme de type naissances et morts multiples. Nous montrons notamment que cette approche ne nécessite pas un temps de calcul prohibitif, grâce à la puissance de calcul d’OpenGL qui s’appuie sur la carte graphique. Les premiers résultats obtenus montrent la pertinence de l’approche adoptée. En particulier, elle permet de résoudre des ambiguïtés pour lesquelles l’inversion du problème serait quasiment impossible. Abstract : In this paper, contrary to the classical approach addressing the 3D reconstruction problem as an inverse problem and solving it by matching two images from a stereoscopic pair, we show that we can solve the direct problem in a simpler way. To do so, we randomly propose configurations of buildings while keeping only the most relevant ones, using a multiple births and deaths algorithm. Notably, we show that this approach does not imply a prohibitory computation time, thanks to the freeware OpenGL which exploits the graphic card. The first results show that the proposed approach is relevant. In particular, it allows solving ambiguities for which inverting the problem is almost impossible.

6 - A novel algorithm for occlusions and perspective effects using a 3d object process. A. Gamal Eldin et X. Descombes et J. Zerubia. Dans ICASSP 2011 (International Conference on Acoustics, Speech and Signal Processing), Prague, Czech Republic, mai 2011. Mots-clés : Occlusions, 3D object process, multiple object extraction, Multiple Birth and Death, Penguins Counting. @INPROCEEDINGS{ICASSP_2011, author = {Gamal Eldin, A. and Descombes, X. and Zerubia, J.}, title = {A novel algorithm for occlusions and perspective effects using a 3d object process}, year = {2011}, month = {mai}, booktitle = {ICASSP 2011 (International Conference on Acoustics, Speech and Signal Processing)}, address = {Prague, Czech Republic}, url = {http://hal.inria.fr/inria-00592449/fr/}, keyword = {Occlusions, 3D object process, multiple object extraction, Multiple Birth and Death, Penguins Counting} } Abstract : In this paper, we introduce a novel probabilistic approach to handle occlusions and perspective effects. The proposed method is an object based method embedded in a marked point process framework. We apply it for the size estimation of a penguin colony, where we model a penguin colony as an unknown number of 3D objects. The main idea of the proposed approach is to sample some candidate configurations consisting of 3D objects lying in the real plane. A Gibbs energy is define on the configuration space, which takes into account both prior and data information. These configurations are projected onto the image plane. The configurations are modified until convergence using the multiple birth and death optimization algorithm and by measuring the similarity between the projected image of the configuration and the real image. During optimization, the proposed configuration is modeled by a mixed graph which represents all dependencies between the objects, including interaction between neighbor objects and parent-child dependency for occluded objects. We tested our model on synthetic image, and real images.

7 - Brain tumor vascular network segmentation from micro-tomography. X. Descombes et F. Plouraboue et El Boustani Habdelhkim et Fonta Caroline et |LeDuc Geraldine et Serduc Raphael et Weitkamp Timm. Dans Internation Symposium of Biomedical Imaging (ISBI), Chicago, USA, avril 2011. Mots-clés : Segmentation, Markov random field, Tomography, Brain, vascular network. Copyright : IEEE @INPROCEEDINGS{isbi11, author = {Descombes, X. and Plouraboue, F. and Boustani Habdelhkim, El and Caroline, Fonta and Geraldine, |LeDuc and Raphael, Serduc and Timm, Weitkamp}, title = {Brain tumor vascular network segmentation from micro-tomography}, year = {2011}, month = {avril}, booktitle = {Internation Symposium of Biomedical Imaging (ISBI)}, address = {Chicago, USA}, url = {http://dx.doi.org/10.1109/ISBI.2011.5872596}, keyword = {Segmentation, Markov random field, Tomography, Brain, vascular network} } Abstract : Micro-tomography produces high resolution images of biological structures such as vascular networks. In this paper, we present a new approach for segmenting vascular network into pathological and normal regions from considering their micro-vessel 3D structure only. We define and use a conditional random field for segmenting the output of a watershed algorithm. The tumoral and normal classes are thus characterized by their respective distribution of watershed region size interpreted as local vascular territories.

8 - Multiple Birth and Cut Algorithm for Point Process Optimization. A. Gamal Eldin et X. Descombes et J. Zerubia. Dans Proc. IEEE International Conference on Signal-Image Technology and Internet-based Systems (SITIS), Kuala Lumpur, Malaysia, décembre 2010. Mots-clés : Multiple Birth and Cut, Graph Cut, Multiple Birth and Death, Processus ponctuels marques. @INPROCEEDINGS{MBC_MPP_SITIS10, author = {Gamal Eldin, A. and Descombes, X. and Zerubia, J.}, title = {Multiple Birth and Cut Algorithm for Point Process Optimization}, year = {2010}, month = {décembre}, booktitle = {Proc. IEEE International Conference on Signal-Image Technology and Internet-based Systems (SITIS)}, address = {Kuala Lumpur, Malaysia}, url = {http://hal.archives-ouvertes.fr/inria-00516305/fr/}, keyword = {Multiple Birth and Cut, Graph Cut, Multiple Birth and Death, Processus ponctuels marques} } Abstract : In this paper, we describe a new optimization method which we call Multiple Birth and Cut (MBC). It combines the recently developed Multiple Birth and Death (MBD) algorithm and the Graph-Cut algorithm. MBD and MBC optimization methods are applied to the energy minimization of an object based model, the marked point process. We compare the MBC to the MBD showing the advantages and disadvantages, where the most important advantage is the reduction of the number of parameters. We validated our algorithm on the counting problem of flamingos in colony, where our algorithm outperforms the performance of the MBD algorithm.

9 - Parameter estimation for a marked point process within a framework of multidimensional shape extraction from remote sensing images. S. Ben Hadj et F. Chatelain et X. Descombes et J. Zerubia. Dans Proc. ISPRS Technical Commission III Symposium on Photogrammetry Computer Vision and Image Analysis (PCV), Paris, France, septembre 2010. Mots-clés : Shape extraction, Processus ponctuels marques, RJMCMC, Recuit Simule, EM Stochastique (SEM). @INPROCEEDINGS{sbenhadj10a, author = {Ben Hadj, S. and Chatelain, F. and Descombes, X. and Zerubia, J.}, title = {Parameter estimation for a marked point process within a framework of multidimensional shape extraction from remote sensing images}, year = {2010}, month = {septembre}, booktitle = {Proc. ISPRS Technical Commission III Symposium on Photogrammetry Computer Vision and Image Analysis (PCV)}, address = {Paris, France}, url = {http://hal.archives-ouvertes.fr/docs/00/52/63/45/PDF/ISPRS_SBH_FC_XD_JZ_Final2.pdf}, keyword = {Shape extraction, Processus ponctuels marques, RJMCMC, Recuit Simule, EM Stochastique (SEM)} }

10 - Tree crown detection in high resolution optical and LiDAR images of tropical forest. J. Zhou et C. Proisy et X. Descombes et I. Hedhli et N. Barbier et J. Zerubia et J.-P. Gastellu-Etchegorry et P. Couteron. Dans Proc. SPIE Symposium on Remote Sensing, Toulouse, France, septembre 2010. Mots-clés : Tropical forest, tree detection, Marked point process. @INPROCEEDINGS{Zhou10, author = {Zhou, J. and Proisy, C. and Descombes, X. and Hedhli, I. and Barbier, N. and Zerubia, J. and Gastellu-Etchegorry, J.-P. and Couteron, P.}, title = {Tree crown detection in high resolution optical and LiDAR images of tropical forest}, year = {2010}, month = {septembre}, booktitle = {Proc. SPIE Symposium on Remote Sensing}, address = {Toulouse, France}, url = {http://dx.doi.org/10.1117/12.865068}, keyword = {Tropical forest, tree detection, Marked point process} }

11 - Multi-spectral Image Analysis for Skin Pigmentation Classification. S. Prigent et X. Descombes et D. Zugaj et P. Martel et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Hong-Kong, China, septembre 2010. Mots-clés : skin hyper-pigmentation, Multi-spectral images, Support Vector Machines, Independant Component Analysis, Data reduction. @INPROCEEDINGS{sp02, author = {Prigent, S. and Descombes, X. and Zugaj, D. and Martel, P. and Zerubia, J.}, title = {Multi-spectral Image Analysis for Skin Pigmentation Classification}, year = {2010}, month = {septembre}, booktitle = {Proc. IEEE International Conference on Image Processing (ICIP)}, address = {Hong-Kong, China}, pdf = {http://hal.inria.fr/docs/00/49/94/92/PDF/Article_ICIP.pdf}, keyword = {skin hyper-pigmentation, Multi-spectral images, Support Vector Machines, Independant Component Analysis, Data reduction} } Abstract : In this paper, we compare two different approaches for semi-automatic detection of skin hyper-pigmentation on multi-spectral images. These two methods are support vector machine (SVM) and blind source separation. To apply SVM, a dimension reduction method adapted to data classification is proposed. It allows to improve the quality of SVM classification as well as to have reasonable computation time. For the blind source separation approach we show that, using independent component analysis, it is possible to extract a relevant cartography of skin pigmentation.

12 - Building Detection in a Single Remotely Sensed Image with a Point Process of Rectangles. C. Benedek et X. Descombes et J. Zerubia. Dans Proc. International Conference on Pattern Recognition (ICPR), Istanbul, Turkey, août 2010. Mots-clés : Processus ponctuels marques, multiple birth-and-death dynamics, Building extraction. @INPROCEEDINGS{benedekICPR10, author = {Benedek, C. and Descombes, X. and Zerubia, J.}, title = {Building Detection in a Single Remotely Sensed Image with a Point Process of Rectangles}, year = {2010}, month = {août}, booktitle = {Proc. International Conference on Pattern Recognition (ICPR)}, address = {Istanbul, Turkey}, pdf = {http://hal.archives-ouvertes.fr/inria-00481019/en/}, keyword = {Processus ponctuels marques, multiple birth-and-death dynamics, Building extraction} } Abstract : In this paper we introduce a probabilistic approach of building extraction in remotely sensed images. To cope with data heterogeneity we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature based modules. A global optimization process attempts to find the optimal configuration of buildings, considering simultaneously the observed data, prior knowledge, and interactions between the neighboring building parts. The proposed method is evaluated on various aerial image sets containing more than 500 buildings, and the results are matched against two state-of-the-art techniques.

13 - Spectral Analysis and Unsupervised SVM Classification for Skin Hyper-pigmentation Classification. S. Prigent et X. Descombes et D. Zugaj et J. Zerubia. Dans Proc. IEEE Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS), Reykjavik, Iceland, juin 2010. Mots-clés : Sectral analysis, Data reduction, Projection pursuit, Support Vector Machines, skin hyper-pigmentation. @INPROCEEDINGS{sp01, author = {Prigent, S. and Descombes, X. and Zugaj, D. and Zerubia, J.}, title = {Spectral Analysis and Unsupervised SVM Classification for Skin Hyper-pigmentation Classification}, year = {2010}, month = {juin}, booktitle = {Proc. IEEE Workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing (WHISPERS)}, address = {Reykjavik, Iceland}, pdf = {http://hal.inria.fr/docs/00/49/55/60/PDF/whispers2010_submission_124.pdf}, keyword = {Sectral analysis, Data reduction, Projection pursuit, Support Vector Machines, skin hyper-pigmentation} } Abstract : Data reduction procedures and classification via support vector machines (SVMs) are often associated with multi or hyperspectral image analysis. In this paper, we propose an automatic method with these two schemes in order to perform a classification of skin hyper-pigmentation on multi-spectral images. We propose a spectral analysis method to partition the spectrum as a tool for data reduction, implemented by projection pursuit. Once the data is reduced, an SVM is used to differentiate the pathological from the healthy areas. As SVM is a supervised classification method, we propose a spatial criterion for spectral analysis in order to perform automatic learning.

14 - Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours. M. S. Kulikova et I. H. Jermyn et X. Descombes et E. Zhizhina et J. Zerubia. Dans Proc. IS&T/SPIE Electronic Imaging, San Jose, USA, janvier 2010. Mots-clés : Extraction d'objets, Processus ponctuels marques, Shape prior, Contour actif, birth-and-death dynamics. Copyright : Copyright 2010 by SPIE and IS&T. This paper was published in the proceedings of IS&T/SPIE Electronic Imaging 2010 Conference in San Jose, USA, and is made available as an electronic reprint with permission of SPIE and IS&T. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. @INPROCEEDINGS{Kulikova10a, author = {Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, title = {Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours}, year = {2010}, month = {janvier}, booktitle = {Proc. IS&T/SPIE Electronic Imaging}, address = {San Jose, USA}, pdf = {http://hal.archives-ouvertes.fr/docs/00/46/54/72/PDF/Kulikova_SPIE2010.pdf}, keyword = {Extraction d'objets, Processus ponctuels marques, Shape prior, Contour actif, birth-and-death dynamics} } Abstract : We extend the marked point process models that have been used for object extraction from images to arbitrarily shaped objects, without greatly increasing the computational complexity of sampling and estimation. From an alternative point of view, the approach can be viewed as an extension of the active contour methodology to an a priori unknown number of objects. Sampling and estimation are based on a stochastic birth-and-death process defined on the configuration space of an arbitrary number of objects, where the objects are defined by the image data and prior information. The performance of the approach is demonstrated via experimental results on synthetic and real data.

15 - A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects. M. S. Kulikova et I. H. Jermyn et X. Descombes et E. Zhizhina et J. Zerubia. Dans Proc. IEEE SITIS, Publ. IEEE Computer Society, Marrakech, Maroc, décembre 2009. Mots-clés : Extraction d'objets, Processus ponctuels marques, Shape prior, Contour actif, multiple birth-and-death dynamics. @INPROCEEDINGS{Kulikova09a, author = {Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, title = {A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects}, year = {2009}, month = {décembre}, booktitle = {Proc. IEEE SITIS}, publisher = {IEEE Computer Society}, address = {Marrakech, Maroc}, pdf = {http://hal.inria.fr/docs/00/43/63/20/PDF/PID1054029.pdf}, keyword = {Extraction d'objets, Processus ponctuels marques, Shape prior, Contour actif, multiple birth-and-death dynamics} } Abstract : We define a method for incorporating strong prior shape information into a recently extended Markov point process model for the extraction of arbitrarily-shaped objects from images. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process defined in a space of multiple objects. The single objects considered are defined by both the image data and the prior information in a way that controls the computational complexity of the estimation problem. The method is tested via experiments on a very high resolution aerial image of a scene composed of tree crowns.

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