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Adaptive Simulated Annealing for Energy Minimization Problem in a Marked Point Process Application

  • Guillaume Perrin
  • Xavier Descombes
  • Josiane Zerubia
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3757)

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.

Keywords

Simulated Annealing Critical Zone Acceptance Ratio Cooling Schedule Marked Point Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Guillaume Perrin
    • 1
    • 2
  • Xavier Descombes
    • 2
  • Josiane Zerubia
    • 2
  1. 1.Mas LaboratoryEcole Centrale ParisChatenay-MalabryFrance
  2. 2.Ariana, joint research group INRIA/I3SINRIA Sophia AntipolisSophia Antipolis CedexFrance

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