Adaptive simulated annealing for energy minimization problem in a marked point process application

Authors:
Guillaume Perrin;Xavier Descombes;Josiane Zerubia
Affiliations:
,Mas Laboratory, Ecole Centrale Paris, Chatenay-Malabry, France;Ariana, joint research group INRIA/I3S, INRIA Sophia Antipolis, Sophia Antipolis Cedex, France;Ariana, joint research group INRIA/I3S, INRIA Sophia Antipolis, Sophia Antipolis Cedex, France
Venue:
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Year:
2005

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Abstract

We use marked point processes to detect an unknown number of trees from high resolution aerial images. This is in fact an energy minimization problem, where the energy contains a prior term which takes into account the geometrical properties of the objects, and a data term to match these objects to the image. This stochastic process is simulated via a Reversible Jump Markov Chain Monte Carlo procedure, which embeds a Simulated Annealing scheme to extract the best configuration of objects. We compare here different cooling schedules of the Simulated Annealing algorithm which could provide some good minimization in a short time. We also study some adaptive proposition kernels.