Building Detection by Markov Object processes and a MCMC Algorithm

Laurent Garcin 1 Xavier Descombes Josiane Zerubia Hervé Le Men
1 ARIANA - Inverse problems in earth monitoring
CRISAM - Inria Sophia Antipolis - Méditerranée , SIS - Signal, Images et Systèmes
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.
Type de document :
Rapport
RR-4206, INRIA. 2001


https://hal.inria.fr/inria-00072416
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Soumis le : mercredi 24 mai 2006 - 09:54:16
Dernière modification le : mercredi 31 mai 2006 - 14:24:26
Document(s) archivé(s) le : dimanche 4 avril 2010 - 20:53:31

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Laurent Garcin, Xavier Descombes, Josiane Zerubia, Hervé Le Men. Building Detection by Markov Object processes and a MCMC Algorithm. RR-4206, INRIA. 2001. <inria-00072416>

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