Publications of Xavier Descombes

Result of the query in the list of publications :

• 44 Articles
• 1 PhD Thesis and Habilitation
• 97 Conference articles
• 36 Technical and Research Reports
• 7 Collection articles or Books chapters
• 2 Books

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44 Articles

1 - Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics. C. Benedek and X. Descombes and J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 34(1): pages 33-50, January 2012. Keywords : Building extraction, Change detection, Marked point process, multiple birth-and-death dynamics. Copyright : IEEE @ARTICLE{benedekPAMI11, author = {Benedek, C. and Descombes, X. and Zerubia, J.}, title = {Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics}, year = {2012}, month = {January}, journal = {IEEE Trans. Pattern Analysis and Machine Intelligence}, volume = {34}, number = {1}, pages = {33-50}, url = {http://dx.doi.org/10.1109/TPAMI.2011.94}, keyword = {Building extraction, Change detection, Marked point process, multiple birth-and-death dynamics} } Abstract : In this paper we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. We present methodological contributions in three key issues: (1) We implement a novel object-change modeling approach based on Multitemporal Marked Point Processes, which simultaneously exploits low level change information between the time layers and object level building description to recognize and separate changed and unaltered buildings. (2) To answering the challenges of data heterogeneity in aerial and satellite image repositories, we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature based modules. (3) To simultaneously ensure the convergence, optimality and computation complexity constraints raised by the increased data quantity, we adopt the quick Multiple Birth and Death optimization technique for change detection purposes, and propose a novel non-uniform stochastic object birth process, which generates relevant objects with higher probability based on low-level image features.

2 - An automatic counter for aerial images of aggregations of large birds. S. Descamps and A. Béchet and X. Descombes and A. Arnaud and J. Zerubia. Bird Study, : pages 1-7, June 2011. @ARTICLE{BirdStudy, author = {Descamps, S. and Béchet, A. and Descombes, X. and Arnaud, A. and Zerubia, J.}, title = {An automatic counter for aerial images of aggregations of large birds}, year = {2011}, month = {June}, journal = {Bird Study}, pages = {1-7}, url = {http://hal.inria.fr/inria-00624587}, pdf = {http://www-sop.inria.fr/ariana/Publis/Descamps2011BS.pdf}, keyword = {} }

3 - Multiple Birth and Cut Algorithm for Multiple Object Detection. A. Gamal Eldin and X. Descombes and Charpiat G. and J. Zerubia. Journal of Multimedia Processing and Technologies, 2011. Keywords : Markov point process, Multiple Birth and Cut, Graph Cut, Belief Propagation, flamingo counting. @ARTICLE{MBC_BP10, author = {Gamal Eldin, A. and Descombes, X. and G., Charpiat and Zerubia, J.}, title = {Multiple Birth and Cut Algorithm for Multiple Object Detection}, year = {2011}, journal = {Journal of Multimedia Processing and Technologies}, url = {http://hal.inria.fr/hal-00616371}, keyword = {Markov point process, Multiple Birth and Cut, Graph Cut, Belief Propagation, flamingo counting} } 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 energy minimization of an object based model, the marked point process. We compare the MBC to the MBD showing their respective advantages and drawbacks, where the most important advantage of the MBC is the reduction of number of parameters. We demonstrate that by proposing good candidates throughout the selection phase in the birth step, the speed of convergence is increased. In this selection phase, the best candidates are chosen from object sets by a belief propagation algorithm. We validate our algorithm on the flamingo counting problem in a colony and demonstrate that our algorithm outperforms the MBD algorithm.

4 - A Marked Point Process Model Including Strong Prior Shape Information Applied to Multiple Object Extraction From Images. M. S. Kulikova and I. H. Jermyn and X. Descombes and E. Zhizhina and J. Zerubia. International Journal of Computer Vision and Image Processing, 1(2): pages 1-12, 2011. Keywords : Active contour, Marked point process, multiple birth-and-death dynamics, multiple object extraction, Shape prior. @ARTICLE{kulikova_ijcvip2010, author = {Kulikova, M. S. and Jermyn, I. H. and Descombes, X. and Zhizhina, E. and Zerubia, J.}, title = {A Marked Point Process Model Including Strong Prior Shape Information Applied to Multiple Object Extraction From Images}, year = {2011}, journal = {International Journal of Computer Vision and Image Processing}, volume = {1}, number = {2}, pages = {1-12}, url = {http://hal.archives-ouvertes.fr/hal-00804118}, keyword = {Active contour, Marked point process, multiple birth-and-death dynamics, multiple object extraction, Shape prior} } Abstract : Object extraction from images is one of the most important tasks in remote sensing image analysis. For accurate extraction from very high resolution (VHR) images, object geometry needs to be taken into account. A method for incorporating strong yet flexible prior shape information into a marked point process model for the extraction of multiple objects of complex shape is presented. To control the computational complexity, the objects considered are defined using the image data and the prior shape information. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process on the space of multiple objects. The authors present several experimental results on the extraction of tree crowns from VHR aerial images.

5 - Approche non supervisée par processus ponctuels marqués pour l'extraction d'objets à partir d'images aériennes et satellitaires. S. Ben Hadj and F. Chatelain and X. Descombes and J. Zerubia. Revue Française de Photogrammétrie et de Télédétection (SFPT), (194): pages 2-15, 2011. Keywords : processus ponctuel marqué, RJMCMC, Simulated Annealing, SEM, pseudo-vraisemblance, extraction d'objet.. @ARTICLE{RFPT_SBH_11, author = {Ben Hadj, S. and Chatelain, F. and Descombes, X. and Zerubia, J.}, title = {Approche non supervisée par processus ponctuels marqués pour l'extraction d'objets à partir d'images aériennes et satellitaires}, year = {2011}, journal = {Revue Française de Photogrammétrie et de Télédétection (SFPT)}, number = {194}, pages = {2-15}, url = {http://hal.inria.fr/hal-00638665}, keyword = {processus ponctuel marqué, RJMCMC, Simulated Annealing, SEM, pseudo-vraisemblance, extraction d'objet.} }

6 - Geometric Feature Extraction by a Multi-Marked Point Process . F. Lafarge and G. Gimel'farb and X. Descombes. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(9): pages 1597-1609, September 2010. Keywords : Shape extraction, Spatial point process, Stochastic geometry, fast optimization, Texture, remote sensing. @ARTICLE{pami09b_lafarge, author = {Lafarge, F. and Gimel'farb, G. and Descombes, X.}, title = {Geometric Feature Extraction by a Multi-Marked Point Process }, year = {2010}, month = {September}, journal = {IEEE Trans. Pattern Analysis and Machine Intelligence}, volume = {32}, number = {9}, pages = {1597-1609}, url = {http://dx.doi.org/10.1109/TPAMI.2009.152}, keyword = {Shape extraction, Spatial point process, Stochastic geometry, fast optimization, Texture, remote sensing} } Abstract : This paper presents a new stochastic marked point process for describing images in terms of a finite library of geometric objects. Image analysis based on conventional marked point processes has already produced convincing results but at the expense of parameter tuning, computing time, and model specificity. Our more general multimarked point process has simpler parametric setting, yields notably shorter computing times, and can be applied to a variety of applications. Both linear and areal primitives extracted from a library of geometric objects are matched to a given image using a probabilistic Gibbs model, and a Jump-Diffusion process is performed to search for the optimal object configuration. Experiments with remotely sensed images and natural textures show that the proposed approach has good potential. We conclude with a discussion about the insertion of more complex object interactions in the model by studying the compromise between model complexity and efficiency.

7 - Unsupervised line network extraction in remote sensing using a polyline process. C. Lacoste and X. Descombes and J. Zerubia. Pattern Recognition, 43(4): pages 1631-1641, April 2010. Keywords : Marked point process, Line networks, Road network extraction. @ARTICLE{lacoste10, author = {Lacoste, C. and Descombes, X. and Zerubia, J.}, title = {Unsupervised line network extraction in remote sensing using a polyline process}, year = {2010}, month = {April}, journal = {Pattern Recognition}, volume = {43}, number = {4}, pages = {1631-1641}, url = {http://dx.doi.org/10.1016/j.patcog.2009.11.003}, keyword = {Marked point process, Line networks, Road network extraction} } Abstract : Marked point processes provide a rigorous framework to describe a scene by an unordered set of objects. The efficiency of this modeling has been shown on line network extraction with models manipulating interacting segments. In this paper, we extend this previous modeling to polylines composed of an unknown number of segments. Optimization is done via simulated annealing using a Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm. We accelerate the convergence of the algorithm by using appropriate proposal kernels. Results on aerial and satellite images show that this new model outperforms the previous one.

8 - Structural approach for building reconstruction from a single DSM. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(1): pages 135-147, January 2010. @ARTICLE{lafarge_pami09, author = {Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, title = {Structural approach for building reconstruction from a single DSM}, year = {2010}, month = {January}, journal = {IEEE Trans. Pattern Analysis and Machine Intelligence}, volume = {32}, number = {1}, pages = {135-147}, url = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.281}, keyword = {} } Abstract : We present a new approach for building reconstruction from a single Digital Surface Model (DSM). It treats buildings as an assemblage of simple urban structures extracted from a library of 3D parametric blocks (like a LEGO set). First, the 2D-supports of the urban structures are extracted either interactively or automatically. Then, 3D-blocks are placed on the 2D-supports using a Gibbs model which controls both the block assemblage and the fitting to data. A Bayesian decision finds the optimal configuration of 3D--blocks using a Markov Chain Monte Carlo sampler associated with original proposition kernels. This method has been validated on multiple data set in a wide-resolution interval such as 0.7 m satellite and 0.1 m aerial DSMs, and provides 3D representations on complex buildings and dense urban areas with various levels of detail.

9 - A Point Process for Fully Automatic Road Network Detection in Satellite and Aerial Images. P. Cariou and X. Descombes and E. Zhizhina. Problems of Information Transmission, 10(3): pages 247-256, 2010. Keywords : Marked point process, birth and death process, Road network extraction. @ARTICLE{cariou2010, author = {Cariou, P. and Descombes, X. and Zhizhina, E.}, title = {A Point Process for Fully Automatic Road Network Detection in Satellite and Aerial Images}, year = {2010}, journal = {Problems of Information Transmission}, volume = {10}, number = {3}, pages = {247-256}, url = { http://www.jip.ru/2010/247-256-2010.pdf}, keyword = {Marked point process, birth and death process, Road network extraction} }

10 - Comparative study on the performance of multi paramater SAR data for operational urban areas extraction. C. Corbane and N. Baghdadi and X. Descombes and M. Petit. IEEE-Geoscience and Remote Sensing Letters, 6(4): pages 728-732, October 2009. Keywords : Markov random field model, synthetic aperture radar, urban remote sensing. @ARTICLE{COR-09, author = {Corbane, C. and Baghdadi, N. and Descombes, X. and Petit, M.}, title = {Comparative study on the performance of multi paramater SAR data for operational urban areas extraction}, year = {2009}, month = {October}, journal = {IEEE-Geoscience and Remote Sensing Letters}, volume = {6}, number = {4}, pages = {728-732}, url = {http://dx.doi.org/10.1109/LGRS.2009.2024225}, keyword = {Markov random field model, synthetic aperture radar, urban remote sensing} } Abstract : The advent of a new generation of synthetic aperture radar (SAR) satellites, such as Advanced SAR/Environmental Satellite (C-band), Phased Array Type L-band Synthetic Aperture Radar/Advanced Land Observing Satellite (L-band), and TerraSAR-X (X-band), offers advanced potentials for the detection of urban tissue. In this letter, we analyze and compare the performance of multiple types of SAR images in terms of band frequency, polarization, incidence angle, and spatial resolution for the purpose of operational urban areas delineation. As a reference for comparison, we use a proven method for extracting textural features based on a Gaussian Markov Random Field (GMRF) model. The results of urban areas delineation are quantitatively analyzed allowing performing intrasensor and intersensors comparisons. Sensitivity of the GMRF model with respect to texture window size and to spatial resolutions of SAR images is also investigated. Intrasensor comparison shows that polarization and incidence angle play a significant role in the potential of the GMRF model for the extraction of urban areas from SAR images. Intersensors comparison evidences the better performances of X-band images, acquired at 1-m spatial resolution, when resampled to resolutions of 5 and 10 m.

11 - Détection de flamants roses par processus ponctuels marqués pour l'estimation de la taille des populations. S. Descamps and X. Descombes and A. Béchet and J. Zerubia. Traitement du Signal, 26(2): pages 95-108, July 2009. Keywords : flamants roses. @ARTICLE{flamTS, author = {Descamps, S. and Descombes, X. and Béchet, A. and Zerubia, J.}, title = {Détection de flamants roses par processus ponctuels marqués pour l'estimation de la taille des populations}, year = {2009}, month = {July}, journal = {Traitement du Signal}, volume = {26}, number = {2}, pages = {95-108}, pdf = {http://documents.irevues.inist.fr/handle/2042/28809}, keyword = {flamants roses} } Résumé : Nous présentons dans cet article une nouvelle technique de détection de flamants roses sur des images aériennes. Nous considérons une approche stochastique fondée sur les processus ponctuels marqués, aussi appelés processus objets. Ici, les objets représentent les flamants, qui sont modélisés par des ellipses. La densité associée au processus ponctuel marqué d'ellipses est définie par rapport à une mesure de Poisson. Dans un cadre gibbsien, le problème se réduit à la minimisation d'une énergie, qui est constituée d'un terme de régularisation (densité a priori), qui introduit des contraintes sur les objets et leurs interactions; et un terme d'attache aux données, qui permet de localiser sur l'image les flamants à extraire. Nous échantillonnons le processus pour extraire la configuration d'objets minimisant l'énergie grâce à une nouvelle dynamique de Naissances et Morts multiples, amenant finalement à une estimation du nombre total de flamants présents sur l'image. Cette approche donne des comptes avec une bonne précision comparée aux comptes manuels. De plus, elle ne nécessite aucun traitement préalable ou intervention manuelle, ce qui réduit considérablement le temps d'obtention des comptes.

12 - Object Extraction Using a Stochastic Birth-and-Death Dynamics in Continuum. X. Descombes and R. Minlos and E. Zhizhina. Journal of Mathematical Imaging and Vision, 33(3): pages 347-359, 2009. Keywords : birth and death process, Marked point process, Object extraction. Copyright : Springer @ARTICLE{DZM08, author = {Descombes, X. and Minlos, R. and Zhizhina, E.}, title = {Object Extraction Using a Stochastic Birth-and-Death Dynamics in Continuum}, year = {2009}, journal = {Journal of Mathematical Imaging and Vision}, volume = {33}, number = {3}, pages = {347-359}, pdf = {http://dx.doi.org/10.1007/s10851-008-0117-y}, keyword = {birth and death process, Marked point process, Object extraction} } Abstract : We define a new birth and death dynamics dealing with configurations of disks in the plane. We prove the convergence of the continuous process and propose a discrete scheme converging to the continuous case. This framework is developed to address image processing problems consisting in detecting a configuration of objects from a digital image. The derived algorithm is applied for tree crown extraction and bird detection from aerial images. The performance of this approach is shown on real data.

13 - Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Journal of Photogrammetry and Remote Sensing, 63(3): pages 365-381, May 2008. Keywords : Building extraction, 3D reconstruction, Digital Elevation Model, Stochastic geometry. @ARTICLE{lafarge_jprs08, author = {Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, title = {Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling}, year = {2008}, month = {May}, journal = {Journal of Photogrammetry and Remote Sensing}, volume = {63}, number = {3}, pages = {365-381}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/2008_lafarge_jprs08.pdf}, keyword = {Building extraction, 3D reconstruction, Digital Elevation Model, Stochastic geometry} } Abstract : In this paper, we present an automatic building extraction method from Digital Elevation Models based on an object approach. First, a rough approximation of the building footprints is realized by a method based on marked point processes: the building footprints are modeled by rectangle layouts. Then, these rectangular footprints are regularized by improving the connection between the neighboring rectangles and detecting the roof height discontinuities. The obtained building footprints are structured footprints: each element represents a specific part of an urban structure. Results are finally applied to a 3D-city modeling process.

14 - Gap Filling of 3-D Microvascular Networs by Tensor Voting. L. Risser and F. Plouraboue and X. Descombes. IEEE Trans. Medical Imaging, 27(5): pages 674-687, May 2008. Copyright : @ARTICLE{xavTMI3, author = {Risser, L. and Plouraboue, F. and Descombes, X.}, title = {Gap Filling of 3-D Microvascular Networs by Tensor Voting}, year = {2008}, month = {May}, journal = {IEEE Trans. Medical Imaging}, volume = {27}, number = {5}, pages = {674-687}, pdf = {http://ieeexplore.ieee.org/iel5/42/4497376/04389807.pdf?isnumber=4497376&prod=JNL&arnumber=4389807&arSt=674&ared=687&arAuthor=Risser%2C+L.%3B+Plouraboue%2C+F.%3B+Descombes%2C+X.}, keyword = {} }

15 - A marked point process of rectangles and segments for automatic analysis of Digital Elevation Models.. M. Ortner and X. Descombes and J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 2008. Keywords : Image procressing, Poisson point process, Stochastic geometry, Dense urban area, Digital Elevation Model, land register. Copyright : @ARTICLE{ortner08, author = {Ortner, M. and Descombes, X. and Zerubia, J.}, title = {A marked point process of rectangles and segments for automatic analysis of Digital Elevation Models.}, year = {2008}, journal = {IEEE Trans. Pattern Analysis and Machine Intelligence}, pdf = {http://hal.inria.fr/docs/00/27/88/82/PDF/ortner08.pdf}, keyword = {Image procressing, Poisson point process, Stochastic geometry, Dense urban area, Digital Elevation Model, land register} }

16 - The Gibbs fields approach and related dynamics in image processing. X. Descombes and E. Zhizhina. Condensed Matter Physics, 11(2(54)): pages 293-312, 2008. Copyright : Institute for Condensed Matter @ARTICLE{LNA08, author = {Descombes, X. and Zhizhina, E.}, title = {The Gibbs fields approach and related dynamics in image processing}, year = {2008}, journal = {Condensed Matter Physics}, volume = {11}, number = {2(54)}, pages = {293-312}, keyword = {} }

17 - Building Outline Extraction from Digital Elevation Models using Marked Point Processes. M. Ortner and X. Descombes and J. Zerubia. International Journal of Computer Vision, 72(2): pages 107-132, April 2007. Keywords : RJMCMC, Buildings, Stochastic geometry, Marked point process, Digital Elevation Model (DEM). @ARTICLE{ortner_ijcv_05, author = {Ortner, M. and Descombes, X. and Zerubia, J.}, title = {Building Outline Extraction from Digital Elevation Models using Marked Point Processes}, year = {2007}, month = {April}, journal = {International Journal of Computer Vision}, volume = {72}, number = {2}, pages = {107-132}, url = {http://www.springerlink.com/content/d563v16957427102/?p=873bd324c7c14049a45cc1f2905b5a86&pi=0}, keyword = {RJMCMC, Buildings, Stochastic geometry, Marked point process, Digital Elevation Model (DEM)} }

18 - ant colony optimization for image regularization based on a non-stationary Markov modeling. S. Le Hegarat-Mascle and A. Kallel and X. Descombes. IEEE Trans. on Image Processing, 16(3): pages 865-878, March 2007. Keywords : Markov Random Fields, Ants colonization. @ARTICLE{Ants07, author = {Le Hegarat-Mascle, S. and Kallel, A. and Descombes, X.}, title = {ant colony optimization for image regularization based on a non-stationary Markov modeling}, year = {2007}, month = {March}, journal = {IEEE Trans. on Image Processing}, volume = {16}, number = {3}, pages = {865-878}, keyword = {Markov Random Fields, Ants colonization} } Abstract : Ant colony optimization (ACO) has been proposed as a promising tool for regularization in image classification. The algorithm is applied here in a different way than the classical transposition of the graph color affectation problem. The ants collect information through the image, from one pixel to the others. The choice of the path is a function of the pixel label, favoring paths within the same image segment. We show that this corresponds to an automatic adaptation of the neighborhood to the segment form, and that it outperforms the fixed-form neighborhood used in classical Markov random field regularization techniques. The performance of this new approach is illustrated on a simulated image and on actual remote sensing images

19 - Détection de feux de forêt par analyse statistique d'évènements rares à partir d'images infrarouges thermiques. F. Lafarge and X. Descombes and J. Zerubia and S. Mathieu. Traitement du Signal, 24(1), 2007. Note : copyright Traitement du Signal Keywords : Gaussian Field, Rare event, DT-caracteristic, Intensity peak. @ARTICLE{lafarge_ts06, author = {Lafarge, F. and Descombes, X. and Zerubia, J. and Mathieu, S.}, title = {Détection de feux de forêt par analyse statistique d'évènements rares à partir d'images infrarouges thermiques}, year = {2007}, journal = {Traitement du Signal}, volume = {24}, number = {1}, note = {copyright Traitement du Signal}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/2007_lafarge_ts06.pdf}, keyword = {Gaussian Field, Rare event, DT-caracteristic, Intensity peak} }

20 - Computing Statistics from Man-Made Structures on the Earth's Surface for Indexing Satellite Images. A. Bhattacharya and M. Roux and H. Maitre and I. H. Jermyn and X. Descombes and J. Zerubia. International Journal of Simulation Modelling, 6(2): pages 73--83, 2007. @ARTICLE{Bhattacharya07, author = {Bhattacharya, A. and Roux, M. and Maitre, H. and Jermyn, I. H. and Descombes, X. and Zerubia, J.}, title = {Computing Statistics from Man-Made Structures on the Earth's Surface for Indexing Satellite Images}, year = {2007}, journal = {International Journal of Simulation Modelling}, volume = {6}, number = {2}, pages = {73--83}, url = {http://www.ijsimm.com/Full_Papers/Fulltext2007/text6-2_73-83.pdf}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/2007_Bhattacharya07.pdf}, keyword = {} } Abstract : Indexing and retrieval from remote sensing image databases relies on the extraction of appropriate information from the data about the entity of interest (e.g. land cover type) and on the robustness of this extraction to nuisance variables. Other entities in an image may be strongly correlated with the entity of interest and their properties can therefore be used to characterize this entity. The road network contained in an image is one example. The properties of road networks vary considerably from one geographical environment to another, and they can therefore be used to classify and retrieve such environments. In this paper, we define several such environments, and classify them with the aid of geometrical and topological features computed from the road networks occurring in them. The relative failure of network extraction methods in certain types of urban area obliges us to segment such areas and to add a second set of geometrical and topological features computed from the segmentations. To validate the approach, feature selection and SVM linear kernel classification are performed on the feature set arising from a diverse image database.

21 - Automatic building 3D reconstruction from DEMs. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Revue Française de Photogrammétrie et de Télédétection (SFPT), 184: pages 48--53, 2006. Keywords : 3D-reconstruction, Digital Elevation Model, Building extraction, dense urban areas. @ARTICLE{lafarge_sfpt06, author = {Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, title = {Automatic building 3D reconstruction from DEMs}, year = {2006}, journal = {Revue Française de Photogrammétrie et de Télédétection (SFPT)}, volume = {184}, pages = {48--53}, url = {http://isprs.free.fr/documents/Papers/T07-32.pdf}, keyword = {3D-reconstruction, Digital Elevation Model, Building extraction, dense urban areas} } Abstract : This paper is about an example of PLEIADES applications, the 3D building reconstruction. The future PLEIADES satellites are especially well adapted to deal with 3D building reconstruction through the sub-metric resolution of images and its stereoscopic characteristics. We propose a fully automatic 3D-city model of dense urban areas using a parametric approach. First, a Digital Elevation Model (DEM) is generated using an algorithm based on a maximum-flow formulation using three views. Then, building footprints are extracted from the DEM through an automatic method based on marked point processes : they are represented by an association of rectangles that we regularize by improving the connection of the neighboring rectangles and the facade discontinuity detection. Finally, a 3D-reconstruction method based on a skeleton process which allows to model the rooftops is proposed from the DEM and the building footprints. The different building heights constitute parameters which are estimated and then regularized by the ”K-means” algorithm including an entropy term.

22 - Point Processes for Unsupervised Line Network Extraction in Remote Sensing. C. Lacoste and X. Descombes and J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 27(10): pages 1568-1579, October 2005. @ARTICLE{lacoste05, author = {Lacoste, C. and Descombes, X. and Zerubia, J.}, title = {Point Processes for Unsupervised Line Network Extraction in Remote Sensing}, year = {2005}, month = {October}, journal = {IEEE Trans. Pattern Analysis and Machine Intelligence}, volume = {27}, number = {10}, pages = {1568-1579}, pdf = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=32189&arnumber=1498752&count=18&index=4}, keyword = {} }

23 - Modèle Paramétrique pour la Reconstruction Automatique en 3D de Zones Urbaines Denses à partir d'Images Satellitaires Haute Résolution. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Revue Française de Photogrammétrie et de Télédétection (SFPT), 180: pages 4--12, 2005. Keywords : 3D reconstruction, Urban areas, Bayesian approach, MCMC, Satellite images. Copyright : SFPT @ARTICLE{lafarge_sfpt05, author = {Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, title = {Modèle Paramétrique pour la Reconstruction Automatique en 3D de Zones Urbaines Denses à partir d'Images Satellitaires Haute Résolution}, year = {2005}, journal = {Revue Française de Photogrammétrie et de Télédétection (SFPT)}, volume = {180}, pages = {4--12}, pdf = {ftp://ftp-sop.inria.fr/ariana/Articles/2005_lafarge_sfpt05.pdf}, keyword = {3D reconstruction, Urban areas, Bayesian approach, MCMC, Satellite images} }

24 - Applications of Gibbs fields methods to image processing problems. X. Descombes and E. Zhizhina. Problems of Information Transmission, 40(3): pages 108--125, September 2004. Note : in Russian @ARTICLE{DES04br, author = {Descombes, X. and Zhizhina, E.}, title = {Applications of Gibbs fields methods to image processing problems}, year = {2004}, month = {September}, journal = {Problems of Information Transmission}, volume = {40}, number = {3}, pages = {108--125}, note = {in Russian}, pdf = {http://www.mathnet.ru/php/getFT.phtml?jrnid=ppi&paperid=146&what=fullt&option_lang=rus}, keyword = {} }

25 - Applications of Gibbs fields methods to image processing problems. X. Descombes and E. Zhizhina. Problems of Information Transmission, 40(3): pages 279-295, September 2004. Note : in English @ARTICLE{DES04be, author = {Descombes, X. and Zhizhina, E.}, title = {Applications of Gibbs fields methods to image processing problems}, year = {2004}, month = {September}, journal = {Problems of Information Transmission}, volume = {40}, number = {3}, pages = {279-295}, note = {in English}, url = {http://link.springer.com/article/10.1023%2FB%3APRIT.0000044262.70555.5c}, keyword = {} }

26 - An object based approach for detecting smallbrain lesions: application to Virchow-Robin spaces. X. Descombes and F. Kruggel and G. Wollny and H.J. Gertz. IEEE Trans. Medical Imaging, 23(2): pages 246--255, February 2004. @ARTICLE{DES04a, author = {Descombes, X. and Kruggel, F. and Wollny, G. and Gertz, H.J.}, title = {An object based approach for detecting smallbrain lesions: application to Virchow-Robin spaces}, year = {2004}, month = {February}, journal = {IEEE Trans. Medical Imaging}, volume = {23}, number = {2}, pages = {246--255}, pdf = {http://ieeexplore.ieee.org/iel5/42/28264/01263613.pdf?tp=&arnumber=1263613&isnumber=28264}, keyword = {} }

27 - A Gibbs point process for road extraction in remotely sensed images. R. Stoica and X. Descombes and J. Zerubia. International Journal of Computer Vision, 57(2): pages 121--136, 2004. @ARTICLE{STO04a, author = {Stoica, R. and Descombes, X. and Zerubia, J.}, title = {A Gibbs point process for road extraction in remotely sensed images}, year = {2004}, journal = {International Journal of Computer Vision}, volume = {57}, number = {2}, pages = {121--136}, url = {http://www.springerlink.com/content/kr262t6084464n30/}, keyword = {} }

28 - Texture Feature Analysis Using a Gauss-Markov Model in Hyperspectral Image Classification. G. Rellier and X. Descombes and F. Falzon and J. Zerubia. IEEE Trans. Geoscience and Remote Sensing, 42(7): pages 1543--1551, 2004. @ARTICLE{DES04c, author = {Rellier, G. and Descombes, X. and Falzon, F. and Zerubia, J.}, title = {Texture Feature Analysis Using a Gauss-Markov Model in Hyperspectral Image Classification}, year = {2004}, journal = {IEEE Trans. Geoscience and Remote Sensing}, volume = {42}, number = {7}, pages = {1543--1551}, pdf = {http://ieeexplore.ieee.org/iel5/36/29162/01315838.pdf?tp=&arnumber=1315838&isnumber=29162}, keyword = {} }

29 - Extraction automatique de caricatures de bâtiments a partir de modeles numeriques d'elevation par utilisation de processus ponctuels spatiaux. M. Ortner and X. Descombes and J. Zerubia. Bulletin de la Société Française de Photogrammétrie et de Télédétection, 173-174: pages 83--92, 2004. @ARTICLE{ORT04a, author = {Ortner, M. and Descombes, X. and Zerubia, J.}, title = {Extraction automatique de caricatures de bâtiments a partir de modeles numeriques d'elevation par utilisation de processus ponctuels spatiaux}, year = {2004}, journal = {Bulletin de la Société Française de Photogrammétrie et de Télédétection}, volume = {173-174}, pages = {83--92}, keyword = {} }

30 - A Multiresolution Approach for Shape from Shading Coupling Deterministic and Stochastic Optimization. A. Crouzil and X. Descombes and J.D. Durou. IEEE Trans. Pattern Analysis ans Machine Intelligence, 25(11): pages 1416--1421, November 2003. Note : Special section on `Energy minimization methods in computer vision and pattern recognition' @ARTICLE{crouzilXDJDD, author = {Crouzil, A. and Descombes, X. and Durou, J.D.}, title = {A Multiresolution Approach for Shape from Shading Coupling Deterministic and Stochastic Optimization}, year = {2003}, month = {November}, journal = {IEEE Trans. Pattern Analysis ans Machine Intelligence}, volume = {25}, number = {11}, pages = {1416--1421}, note = {Special section on `Energy minimization methods in computer vision and pattern recognition'}, pdf = {http://ieeexplore.ieee.org/iel5/34/27807/01240116.pdf?tp=&arnumber=1240116&isnumber=27807}, keyword = {} }

31 - Extraction automatique des réseaux linéiques à partir d'images satellitaires et aériennes par processus Markov objet. C. Lacoste and X. Descombes and J. Zerubia and N. Baghdadi. Bulletin de la Société Française de Photogrammétrie et de Télédétection, 170: pages 13--22, 2003. @ARTICLE{lacostesfpt, author = {Lacoste, C. and Descombes, X. and Zerubia, J. and Baghdadi, N.}, title = {Extraction automatique des réseaux linéiques à partir d'images satellitaires et aériennes par processus Markov objet}, year = {2003}, journal = {Bulletin de la Société Française de Photogrammétrie et de Télédétection}, volume = {170}, pages = {13--22}, url = {http://www.researchgate.net/profile/Nicolas_Baghdadi/publication/236882132_Extraction_automatique_des_rseaux_liniques__partir_dimages_satellitaires_et_ariennes_par_processus_Markov_objets/links/00463519e05ebd9e83000000.pdf?disableCoverPage=true}, keyword = {} }

32 - Droplet Shapes for a Class of Models in Z^2 at Zero Temperature. X. Descombes and E. Pechersky. Journal of Statistical Physics, 111(1-2): pages 129--169, 2003. @ARTICLE{descombesEP, author = {Descombes, X. and Pechersky, E.}, title = {Droplet Shapes for a Class of Models in Z^2 at Zero Temperature}, year = {2003}, journal = {Journal of Statistical Physics}, volume = {111}, number = {1-2}, pages = {129--169}, pdf = {http://link.springer.com/article/10.1023/A%3A1022252923753}, keyword = {} }

33 - Classification de Textures Hyperspectrales Fondée sur un Modèle Markovien et Une Technique de Poursuite de Projection. G. Rellier and X. Descombes and F. Falzon and J. Zerubia. Traitement du Signal, 20(1): pages 25--42, 2003. @ARTICLE{rellierXDFFJZ, author = {Rellier, G. and Descombes, X. and Falzon, F. and Zerubia, J.}, title = {Classification de Textures Hyperspectrales Fondée sur un Modèle Markovien et Une Technique de Poursuite de Projection}, year = {2003}, journal = {Traitement du Signal}, volume = {20}, number = {1}, pages = {25--42}, url = {http://documents.irevues.inist.fr/handle/2042/2216}, keyword = {} }

34 - Marked Point Processes in Image Analysis. X. Descombes and J. Zerubia. IEEE Signal Processing Magazine, 19(5): pages 77-84, September 2002. @ARTICLE{XDJZ, author = {Descombes, X. and Zerubia, J.}, title = {Marked Point Processes in Image Analysis}, year = {2002}, month = {September}, journal = {IEEE Signal Processing Magazine}, volume = {19}, number = {5}, pages = {77-84}, pdf = {http://ieeexplore.ieee.org/iel5/79/22084/01028354.pdf?tp=&arnumber=1028354&isnumber=22084}, keyword = {} }

35 - Local registration and deformation of a road cartographic database on a SPOT Satellite Image. G. Rellier and X. Descombes and J. Zerubia. Pattern Recognition, 35(10), 2002. @ARTICLE{rellierXDJZ, author = {Rellier, G. and Descombes, X. and Zerubia, J.}, title = {Local registration and deformation of a road cartographic database on a SPOT Satellite Image}, year = {2002}, journal = {Pattern Recognition}, volume = {35}, number = {10}, url = {http://www.sciencedirect.com/science/article/pii/S0031320301001807}, keyword = {} }

36 - A RJMCMC algorithm for object processes in image processing. X. Descombes and R. Stoica and L. Garcin and J. Zerubia. Monte Carlo Methods and Applications, 7(1-2): pages 149-156, 2001. @ARTICLE{xd01c, author = {Descombes, X. and Stoica, R. and Garcin, L. and Zerubia, J.}, title = {A RJMCMC algorithm for object processes in image processing}, year = {2001}, journal = {Monte Carlo Methods and Applications}, volume = {7}, number = {1-2}, pages = {149-156}, url = {http://www.degruyter.com/view/j/mcma.2001.7.issue-1-2/mcma.2001.7.1-2.149/mcma.2001.7.1-2.149.xml}, keyword = {} }

37 - Mise en correspondance et recalage de graphes~: application aux réseaux routiers extraits d'un couple carte/image. C. Hivernat and X. Descombes and S. Randriamasy and J. Zerubia. Traitement du Signal, 17(1): pages 21-32, 2000. @ARTICLE{xd00, author = {Hivernat, C. and Descombes, X. and Randriamasy, S. and Zerubia, J.}, title = {Mise en correspondance et recalage de graphes~: application aux réseaux routiers extraits d'un couple carte/image}, year = {2000}, journal = {Traitement du Signal}, volume = {17}, number = {1}, pages = {21-32}, url = {http://documents.irevues.inist.fr/handle/2042/2129}, keyword = {} }

38 - Texture analysis through a Markovian modelling and fuzzy classification: Application to urban area Extraction from Satellite Images. A. Lorette and X. Descombes and J. Zerubia. International Journal of Computer Vision, 36(3): pages 221-236, 2000. @ARTICLE{xd00a, author = {Lorette, A. and Descombes, X. and Zerubia, J.}, title = {Texture analysis through a Markovian modelling and fuzzy classification: Application to urban area Extraction from Satellite Images}, year = {2000}, journal = {International Journal of Computer Vision}, volume = {36}, number = {3}, pages = {221-236}, url = {http://dx.doi.org/10.1023/A:1008129103384}, pdf = {http://dx.doi.org/10.1023/A:1008129103384}, keyword = {} }

39 - Comparison of Filtering Methods for fMRI Datasets. F. Kruggel and Y. Von Cramon and X. Descombes. NeuroImage, 10(5): pages 530-543, November 1999. @ARTICLE{xd99d, author = {Kruggel, F. and Von Cramon, Y. and Descombes, X.}, title = {Comparison of Filtering Methods for fMRI Datasets}, year = {1999}, month = {November}, journal = {NeuroImage}, volume = {10}, number = {5}, pages = {530-543}, url = {http://www.sciencedirect.com/science/article/pii/S1053811999904901}, keyword = {} }

40 - Estimation of Markov Random Field prior parameters using Markov chain Monte Carlo Maximum Likelihood. X. Descombes and R. Morris and J. Zerubia and M. Berthod. IEEE Trans. Image Processing, 8(7): pages 954-963, July 1999. Keywords : Markov processes, Monte Carlo methods, Potts model, Image segmentation, Maximum likelihood estimation . @ARTICLE{xd99c, author = {Descombes, X. and Morris, R. and Zerubia, J. and Berthod, M.}, title = {Estimation of Markov Random Field prior parameters using Markov chain Monte Carlo Maximum Likelihood}, year = {1999}, month = {July}, journal = {IEEE Trans. Image Processing}, volume = {8}, number = {7}, pages = {954-963}, pdf = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=16772&arnumber=772239&count=14&index=6}, keyword = {Markov processes, Monte Carlo methods, Potts model, Image segmentation, Maximum likelihood estimation } } Abstract : Developments in statistics now allow maximum likelihood estimators for the parameters of Markov random fields (MRFs) to be constructed. We detail the theory required, and present an algorithm that is easily implemented and practical in terms of computation time. We demonstrate this algorithm on three MRF models-the standard Potts model, an inhomogeneous variation of the Potts model, and a long-range interaction model, better adapted to modeling real-world images. We estimate the parameters from a synthetic and a real image, and then resynthesize the models to demonstrate which features of the image have been captured by the model. Segmentations are computed based on the estimated parameters and conclusions drawn.

41 - A Markov Pixon Information approach for low level image description. X. Descombes and F. Kruggel. IEEE Trans. Pattern Analysis ans Machine Intelligence, 21(6): pages 482-494, June 1999. @ARTICLE{xd99b, author = {Descombes, X. and Kruggel, F.}, title = {A Markov Pixon Information approach for low level image description}, year = {1999}, month = {June}, 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 and M. Sigelle and 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 and F. Kruggel and Y. von Cramon. NeuroImage, 8: pages 340-349, 1998. Keywords : fMRI, Restoration, Markov Fields. 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, Restoration, Markov Fields} }

44 - Spatio-temporal fMRI analysis using Markov Random Fields. X. Descombes and F. Kruggel and Y. Von Cramon. IEEE Trans. Medical Imaging, 17(6): pages 1028-1039, 1998. Note : to appear. Keywords : 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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PhD Thesis and 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, February 2004. Keywords : Markov Fields, Stochastic geometry. @PHDTHESIS{Xdescombes, author = {Descombes, X.}, title = {Méthodes stochastiques en analyse d'image : des champs de Markov aux processus ponctuels marqués}, year = {2004}, month = {February}, 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 = {Markov Fields, Stochastic geometry} }

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97 Conference articles

1 - Tree crown detection in high resolution optical images during the early growth stages of eucalyptus plantations in Brazil. J. Zhou and C. Proisy and X. Descombes and J. Zerubia and G. Le Maire and Y. Nouvellon and P. Couteron. In Asian Conference on Pattern Recognition (ACPR), Beijing, China, November 2011. Keywords : 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 = {November}, 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 and D. Zugaj and X. Descombes and P. Martel and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Brussels, Belgium, September 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 = {September}, 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 and X. Descombes and Charpiat G. and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Brussels, Belgium, September 2011. Keywords : 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 = {September}, 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 and A. Gamal Eldin and F. Plouraboue and C. Fonta and S. Serduc and G. Le Duc and T. Weitkamp. In Proc. GRETSI Symposium on Signal and Image Processing, Bordeaux, France, September 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 = {September}, 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 and X. Descombes and P. Lukashevish and A. Kraushonak. In Proc. GRETSI Symposium on Signal and Image Processing, Bordeaux, France, September 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 = {September}, 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.

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