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

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Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,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.

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Author information

Authors and Affiliations

  1. Mas Laboratory, Ecole Centrale Paris, Grande Voie des Vignes, 92290, Chatenay-Malabry, France

    Guillaume Perrin

  2. Ariana, joint research group INRIA/I3S, INRIA Sophia Antipolis, 2004, route des Lucioles, BP 93, 06902, Sophia Antipolis Cedex, France

    Guillaume Perrin, Xavier Descombes & Josiane Zerubia

Authors
  1. Guillaume Perrin
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  2. Xavier Descombes
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  3. Josiane Zerubia
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Editor information

Editors and Affiliations

  1. Department of CISE, University of Florida, Gainesville, FL, USA

    Anand Rangarajan

  2. University of Florida, 32611, Gainesville, FL, USA

    Baba Vemuri

  3. Department of Statistics, University of California, Los Angeles

    Alan L. Yuille

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© 2005 Springer-Verlag Berlin Heidelberg

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Perrin, G., Descombes, X., Zerubia, J. (2005). Adaptive Simulated Annealing for Energy Minimization Problem in a Marked Point Process Application. In: Rangarajan, A., Vemuri, B., Yuille, A.L. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2005. Lecture Notes in Computer Science, vol 3757. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11585978_1

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  • DOI: https://doi.org/10.1007/11585978_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30287-2

  • Online ISBN: 978-3-540-32098-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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