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

1 - Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics. C. Benedek et X. Descombes et J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 34(1): pages 33-50, janvier 2012. Mots-clés : Building extraction, Change detection, Processus ponctuels marques, 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 = {janvier}, 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, Processus ponctuels marques, 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 et A. Béchet et X. Descombes et A. Arnaud et J. Zerubia. Bird Study, : pages 1-7, juin 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 = {juin}, 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 et X. Descombes et Charpiat G. et J. Zerubia. Journal of Multimedia Processing and Technologies, 2011. Mots-clés : 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 et I. H. Jermyn et X. Descombes et E. Zhizhina et J. Zerubia. International Journal of Computer Vision and Image Processing, 1(2): pages 1-12, 2011. Mots-clés : Contour actif, Processus ponctuels marques, 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 = {Contour actif, Processus ponctuels marques, 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 et F. Chatelain et X. Descombes et J. Zerubia. Revue Française de Photogrammétrie et de Télédétection (SFPT), (194): pages 2-15, 2011. Mots-clés : processus ponctuel marqué, RJMCMC, Recuit Simule, 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, Recuit Simule, SEM, pseudo-vraisemblance, extraction d'objet.} }

6 - Geometric Feature Extraction by a Multi-Marked Point Process . F. Lafarge et G. Gimel'farb et X. Descombes. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(9): pages 1597-1609, septembre 2010. Mots-clés : Shape extraction, Spatial point process, Geometrie stochastique, 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 = {septembre}, 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, Geometrie stochastique, 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 et X. Descombes et J. Zerubia. Pattern Recognition, 43(4): pages 1631-1641, avril 2010. Mots-clés : Processus ponctuels marques, Reseaux lineiques, 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 = {avril}, journal = {Pattern Recognition}, volume = {43}, number = {4}, pages = {1631-1641}, url = {http://dx.doi.org/10.1016/j.patcog.2009.11.003}, keyword = {Processus ponctuels marques, Reseaux lineiques, 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 et X. Descombes et J. Zerubia et M. Pierrot-Deseilligny. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(1): pages 135-147, janvier 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 = {janvier}, 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 et X. Descombes et E. Zhizhina. Problems of Information Transmission, 10(3): pages 247-256, 2010. Mots-clés : 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 et N. Baghdadi et X. Descombes et M. Petit. IEEE-Geoscience and Remote Sensing Letters, 6(4): pages 728-732, octobre 2009. Mots-clés : 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 = {octobre}, 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.

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