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Publications of Xavier Descombes
Result of the query in the list of publications :
97 Conference articles |
96 - Die Vorerarbeitung von fMRI-Daten. F. Kruggel and X. Descombes and Y. von Cramon. In Bildverarbeitung für die Medizin, Algorithmen - Systeme - Anwendungen, Universitätsklinikum der RWTH Aachen, Germany, March 1998.
@INPROCEEDINGS{descombes98b,
|
author |
= |
{Kruggel, F. and Descombes, X. and von Cramon, Y.}, |
title |
= |
{Die Vorerarbeitung von fMRI-Daten}, |
year |
= |
{1998}, |
month |
= |
{March}, |
booktitle |
= |
{Bildverarbeitung für die Medizin, Algorithmen - Systeme - Anwendungen}, |
address |
= |
{Universitätsklinikum der RWTH Aachen, Germany}, |
pdf |
= |
{Articles/Vorerarbeitung.pdf}, |
keyword |
= |
{} |
} |
|
97 - Fully Bayesian image segmentation-an engineering perspective. R. Morris and X. Descombes and J. Zerubia. In Proc. IEEE International Conference on Image Processing (ICIP), Vol. 3, pages 54-57, Santa Barbara, CA, USA, October 1997. Keywords : Bayes methods, Markov processes, Monte Carlo methods, Image sampling, Image segmentation.
@INPROCEEDINGS{MorrisICIP97,
|
author |
= |
{Morris, R. and Descombes, X. and Zerubia, J.}, |
title |
= |
{ Fully Bayesian image segmentation-an engineering perspective}, |
year |
= |
{1997}, |
month |
= |
{October}, |
booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
volume |
= |
{3}, |
pages |
= |
{54-57}, |
address |
= |
{Santa Barbara, CA, USA}, |
pdf |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=631978&isnumber=13718}, |
keyword |
= |
{Bayes methods, Markov processes, Monte Carlo methods, Image sampling, Image segmentation} |
} |
Abstract :
Developments in Markov chain Monte Carlo procedures have made it possible to perform fully Bayesian image segmentation. By this we mean that all the parameters are treated identically, be they the segmentation labels, the class parameters or the Markov random field prior parameters. We perform the analysis by sampling from the posterior distribution of all the parameters. Sampling from the MRF parameters has traditionally been considered if not intractable then at least computationally prohibitive. In the statistics literature there are descriptions of experiments showing that the MRF parameters may be sampled by approximating the partition function. These experiments are all, however, on `toy' problems; for the typical size of image encountered in engineering applications the phase transition behaviour of the models becomes a major limiting factor in the estimation of the partition function. Nevertheless, we show that, with some care, fully Bayesian segmentation can be performed on realistic sized images. We also compare the fully Bayesian approach with the approximate pseudolikelihood method |
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36 Technical and Research Reports |
1 - Estimation des paramètres de modèles de processus ponctuels marqués pour l'extraction d'objets en imagerie spatiale et aérienne haute résolution . S. Ben Hadj and F. Chatelain and X. Descombes and J. Zerubia. Rapport de recherche 7350, INRIA, July 2010. Keywords : Marked point process, RJMCMC, Simulated Annealing, Stochastic EM (SEM), pseudo-vraisemblance, Object extraction.
@TECHREPORT{RR-7350,
|
author |
= |
{Ben Hadj, S. and Chatelain, F. and Descombes, X. and Zerubia, J.}, |
title |
= |
{Estimation des paramètres de modèles de processus ponctuels marqués pour l'extraction d'objets en imagerie spatiale et aérienne haute résolution }, |
year |
= |
{2010}, |
month |
= |
{July}, |
institution |
= |
{INRIA}, |
type |
= |
{Rapport de recherche}, |
number |
= |
{7350}, |
url |
= |
{http://hal.archives-ouvertes.fr/inria-00508431/fr/}, |
keyword |
= |
{Marked point process, RJMCMC, Simulated Annealing, Stochastic EM (SEM), pseudo-vraisemblance, Object extraction} |
} |
|
2 - Building Extraction and Change Detection in Multitemporal Aerial and Satellite Images in a Joint Stochastic Approach. C. Benedek and X. Descombes and J. Zerubia. Research Report 7143, INRIA, Sophia Antipolis, December 2009. Keywords : Change detection, Building extraction, Marked point process, MAP, multiple birth-and-death dynamics.
@TECHREPORT{benedekRR_09,
|
author |
= |
{Benedek, C. and Descombes, X. and Zerubia, J.}, |
title |
= |
{Building Extraction and Change Detection in Multitemporal Aerial and Satellite Images in a Joint Stochastic Approach}, |
year |
= |
{2009}, |
month |
= |
{December}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{7143}, |
address |
= |
{Sophia Antipolis}, |
url |
= |
{http://hal.archives-ouvertes.fr/inria-00426615}, |
keyword |
= |
{Change detection, Building extraction, Marked point process, MAP, multiple birth-and-death dynamics} |
} |
Résumé :
Dans ce rapport, nous proposons une nouvelle méthode probabiliste qui intègre l'extraction de bâtiments et la détection de changements à partir de paires d'images de télédétection. Un algorithme d'optimisation globale permet de trouver la configuration optimale de bâtiments en considérant des observations, des connaissances a priori et des interactions entre des parties voisines de bâtiments. La précision est assurée par une vérification d'un modèle objet bayésien; le coût du calcul est considérablement réduit en utilisant un processus stochastique non-uniforme de naissance d'objets fondé sur des caractéristiques bas-niveaux des images, qui génère des objets pertinents ayant une grande probabilité. |
Abstract :
In this report 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. The accuracy is ensured by a Bayesian object model verification, meanwhile the computational cost is significantly decreased by a non-uniform stochastic object birth process, which proposes relevant objects with higher probability based on low-level image features. |
|
3 - Support Vector Machines for burnt area discrimination. O. Zammit and X. Descombes and J. Zerubia. Research Report 6343, INRIA, November 2007. Keywords : Forest fires, Burnt areas, Satellite images, Support Vector Machines, Classification.
@TECHREPORT{zammit_RR_07,
|
author |
= |
{Zammit, O. and Descombes, X. and Zerubia, J.}, |
title |
= |
{Support Vector Machines for burnt area discrimination}, |
year |
= |
{2007}, |
month |
= |
{November}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{6343}, |
url |
= |
{http://hal.inria.fr/inria-00185101/fr/}, |
pdf |
= |
{http://hal.inria.fr/inria-00185101/fr/}, |
keyword |
= |
{Forest fires, Burnt areas, Satellite images, Support Vector Machines, Classification} |
} |
Résumé :
Ce rapport aborde le problème de l'évaluation des dégâts après un feux de forêt. La détection est effectuée à partir d'une seule image satellite (SPOT 5) acquise après le feu. Afin de détecter les zones brûlées, nous utilisons une approche récente de classification nommée SVM (Séparateurs à Vaste Marge). Cette méthode est comparée aux algorithmes de classification plus conventionnels comme les K-moyennes ou les K-plus proches voisins, qui sont régulièrement utilisés en traitement d'image. Nous proposons également une méthode de classification non supervisée combinant les K-moyennes et les SVM. Les résultats fournis par les différentes techniques sont comparés à des vérités de terrain sur diverses zones brûlées. |
Abstract :
This report addresses the problem of burnt area discrimination using remote sensing images. The detection is based on a single post-fire image acquired by SPOT 5 satellite. To delineate the burnt areas, we use a recent classification method called Support Vectors Machines (SVM). This approach is compared to more conventional classifiers such as K-means or K-nearest neighbours which are widely used in image processing. We also proposed a new automatic classification approach combining K-means and SVM. The results given by the different methods are finally compared to ground truths on various burnt areas |
|
4 - 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. Research Report 6328, INRIA, October 2007. Keywords : Object extraction, modélisation stochastique , Marked point process, dynamique de naissance/mort, environnement, flamants roses.
@TECHREPORT{Descamps-Descombes,
|
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 |
= |
{2007}, |
month |
= |
{October}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{6328}, |
url |
= |
{http://hal.inria.fr/inria-00180811}, |
pdf |
= |
{http://hal.inria.fr/docs/00/18/08/93/PDF/RR-Desc-Desc-Bech-Zeru.pdf}, |
keyword |
= |
{Object extraction, modélisation stochastique , Marked point process, dynamique de naissance/mort, environnement, flamants roses} |
} |
|
5 - An adaptive simulated annealing cooling schedule for object detection in images. M. Ortner and X. Descombes and J. Zerubia. Research Report 6336, INRIA, October 2007. Keywords : Image procressing, Shape extraction, Spatial point process, Simulated Annealing, Adaptive cooling schedule.
@TECHREPORT{Ortner-Descombes,
|
author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
title |
= |
{An adaptive simulated annealing cooling schedule for object detection in images}, |
year |
= |
{2007}, |
month |
= |
{October}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{6336}, |
url |
= |
{https://hal.inria.fr/inria-00181764}, |
pdf |
= |
{https://hal.inria.fr/inria-00181764}, |
keyword |
= |
{Image procressing, Shape extraction, Spatial point process, Simulated Annealing, Adaptive cooling schedule} |
} |
|
6 - Object extraction using a stochastic birth-and-death dynamics in continuum. X. Descombes and R. Minlos and E. Zhizhina. Research Report 6135, INRIA, 2007. Keywords : birth and death process, Stochastic modeling, Wavelets.
@TECHREPORT{RR-6135,
|
author |
= |
{Descombes, X. and Minlos, R. and Zhizhina, E.}, |
title |
= |
{Object extraction using a stochastic birth-and-death dynamics in continuum}, |
year |
= |
{2007}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{6135}, |
url |
= |
{https://hal.inria.fr/inria-00133726}, |
pdf |
= |
{http://hal.inria.fr/inria-00133726}, |
keyword |
= |
{birth and death process, Stochastic modeling, Wavelets} |
} |
Abstract :
We define a new birth and death dynamics dealing with configurations of discs 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 extracting objects. 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. |
|
7 - A structural approach for 3D building reconstruction. F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Research Report 6048, INRIA, November 2006. Keywords : 3D reconstruction, Structural approach, Building, RJMCMC, Viterbi.
@TECHREPORT{Lafarge_rr_6048,
|
author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
title |
= |
{A structural approach for 3D building reconstruction}, |
year |
= |
{2006}, |
month |
= |
{November}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{6048}, |
url |
= |
{https://hal.inria.fr/inria-00114338}, |
pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2006_Lafarge_rr_6048.pdf}, |
keyword |
= |
{3D reconstruction, Structural approach, Building, RJMCMC, Viterbi} |
} |
|
8 - Tree Crown Extraction using a Three States Markov Random Field. X. Descombes and E. Pechersky. Research Report 5982, INRIA, September 2006. Keywords : Markov Fields, Tree Crown Extraction.
@TECHREPORT{Descombes-Pechersky,
|
author |
= |
{Descombes, X. and Pechersky, E.}, |
title |
= |
{Tree Crown Extraction using a Three States Markov Random Field}, |
year |
= |
{2006}, |
month |
= |
{September}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{5982}, |
url |
= |
{https://hal.inria.fr/inria-00097555}, |
pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2006_Descombes-Pechersky.pdf}, |
keyword |
= |
{Markov Fields, Tree Crown Extraction} |
} |
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