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Publications of Herve Le Men
Result of the query in the list of publications :
4 Conference articles |
1 - Remotely sensed image segmentation using an object point process.
S. Drot and H. Le Men and X. Descombes and J. Zerubia. In Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Toulouse, France, July 2003.
@INPROCEEDINGS{drot,
|
| author |
= |
{Drot, S. and Le Men, H. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Remotely sensed image segmentation using an object point process}, |
| year |
= |
{2003}, |
| month |
= |
{July}, |
| booktitle |
= |
{Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, |
| address |
= |
{Toulouse, France}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1294331}, |
| keyword |
= |
{} |
| } |
|
2 - Object Point Processes for Image Segmentation.
S. Drot and X. Descombes and H. Le Men and J. Zerubia. In Proc. International Conference on Pattern Recognition (ICPR), Québec, Canada, August 2002.
@INPROCEEDINGS{drotXD,
|
| author |
= |
{Drot, S. and Descombes, X. and Le Men, H. and Zerubia, J.}, |
| title |
= |
{Object Point Processes for Image Segmentation}, |
| year |
= |
{2002}, |
| month |
= |
{August}, |
| booktitle |
= |
{Proc. International Conference on Pattern Recognition (ICPR)}, |
| address |
= |
{Québec, Canada}, |
| url |
= |
{http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1048453}, |
| keyword |
= |
{} |
| } |
|
3 - Building extraction using a Markov point process.
L. Garcin and X. Descombes and J. Zerubia and H. Le Men. In Proc. IEEE International Conference on Image Processing (ICIP), papier invité, Thessalonique, Grèce, October 2001.
@INPROCEEDINGS{xd01d,
|
| author |
= |
{Garcin, L. and Descombes, X. and Zerubia, J. and Le Men, H.}, |
| title |
= |
{Building extraction using a Markov point process}, |
| year |
= |
{2001}, |
| month |
= |
{October}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{papier invité, Thessalonique, Grèce}, |
| url |
= |
{http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=958555}, |
| keyword |
= |
{} |
| } |
|
4 - Segmentation d'image haute résolution par processus Markov objet.
X. Descombes and S. Drot and M. Imberty and H. Le Men and J. Zerubia. In Séminaire Télédétection à très haute résolution spatiale et analyse d'image, Cemagref, Montpellier, France, 2001.
@INPROCEEDINGS{xd01k,
|
| author |
= |
{Descombes, X. and Drot, S. and Imberty, M. and Le Men, H. and Zerubia, J.}, |
| title |
= |
{Segmentation d'image haute résolution par processus Markov objet}, |
| year |
= |
{2001}, |
| booktitle |
= |
{Séminaire Télédétection à très haute résolution spatiale et analyse d'image, Cemagref}, |
| address |
= |
{Montpellier, France}, |
| url |
= |
{http://cemadoc.irstea.fr/oa/PUB00009549-segmentation-image-haute-resolution-par-processus.html}, |
| keyword |
= |
{} |
| } |
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Technical and Research Report |
1 - Building detection by markov object processes and a MCMC algorithm.
L. Garcin and X. Descombes and J. Zerubia and H. Le Men. Research Report 4206, Inria, France, June 2001.
Keywords : Stochastic geometry, Marked point process, Buildings, RJMCMC.
@TECHREPORT{xd01a,
|
| author |
= |
{Garcin, L. and Descombes, X. and Zerubia, J. and Le Men, H.}, |
| title |
= |
{Building detection by markov object processes and a MCMC algorithm}, |
| year |
= |
{2001}, |
| month |
= |
{June}, |
| institution |
= |
{Inria}, |
| type |
= |
{Research Report}, |
| number |
= |
{4206}, |
| address |
= |
{France}, |
| url |
= |
{https://hal.inria.fr/inria-00072416}, |
| pdf |
= |
{https://hal.inria.fr/file/index/docid/72416/filename/RR-4206.pdf}, |
| ps |
= |
{https://hal.inria.fr/docs/00/07/24/16/PS/RR-4206.ps}, |
| keyword |
= |
{Stochastic geometry, Marked point process, Buildings, RJMCMC} |
| } |
Résumé :
Le but de ce travail est de détecter les bâtiments à partir de photographies aeriennes numériques. Nous modélisons un ensemble de bâtiments par une configuration d'objets. Nous définissons un processus ponctuel sur l'ensemble des configurations qui se décompose en deux parties :
* La première est un modèle a priori sur les configurations qui considère des interactions entre les objets,
* la seconde est un modèle d'attache aux données qui induit la cohérence du résultat avec l'image traitée.
Nous avons ainsi une distribution a posteriori dont nous recherchons la configuration maximale. Pour obtenir ce maximum, nous utilisons une simulatio- n de type MCMC - un algorithme de Metropolis-Hasting-Green- couplée avec un schéma de recuit simulé. Nous testons la méthode décrite à la fois sur des données synthétiques et des images stéréoscopiques réelles. |
Abstract :
This work aims at detecting buildings in digital aerial photographs. Here we model a set of buildings by a configuration of objects. We define a point process on the set of configurations, which splits into two parts :
* the first one is a prior model on the configurations which use interactions between objects,
* the second one is a data model which enforces the coherence with the image.
Thus we have a posterior distribution whose maximum has to be found. In order to achieve this maximum, we use a MCMC simulation - a Metropolis-Hasting- s-Green algorithm - mixed with a simulated annealing. Then we test this method on both synthetic and real stereo-images. |
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