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Publications sur Spatial point process
Résultat de la recherche dans la liste des publications :
Article |
1 - 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. |
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Rapport de recherche et Rapport technique |
1 - An adaptive simulated annealing cooling schedule for object detection in images. M. Ortner et X. Descombes et J. Zerubia. Rapport de Recherche 6336, INRIA, octobre 2007. Mots-clés : Traitement d'image, Shape extraction, Spatial point process, Recuit Simule, 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 |
= |
{octobre}, |
institution |
= |
{INRIA}, |
type |
= |
{Research Report}, |
number |
= |
{6336}, |
url |
= |
{https://hal.inria.fr/inria-00181764}, |
pdf |
= |
{https://hal.inria.fr/inria-00181764}, |
keyword |
= |
{Traitement d'image, Shape extraction, Spatial point process, Recuit Simule, Adaptive cooling schedule} |
} |
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