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Rapport Année : 2001

Building Detection by Markov Object processes and a MCMC Algorithm

Xavier Descombes
Josiane Zerubia
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Hervé Le Men
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Résumé

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.

Domaines

Autre [cs.OH]
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Dates et versions

inria-00072416 , version 1 (24-05-2006)

Identifiants

  • HAL Id : inria-00072416 , version 1

Citer

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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