A fast multiple birth and cut algorithm using belief propagation

Ahmed Gamal Eldin 1 Xavier Descombes 1 Guillaume Charpiat 2 Josiane Zerubia 1
1 ARIANA - Inverse problems in earth monitoring
CRISAM - Inria Sophia Antipolis - Méditerranée , SIS - Signal, Images et Systèmes
Abstract : In this paper, we present a faster version of the newly proposed Multiple Birth and Cut (MBC) algorithm. MBC is an optimization method applied to the energy minimization of an object based model, defined by a marked point process. We show that, by proposing good candidates in the birth step of this algorithm, the speed of convergence is increased. The algorithm starts by generating a dense configuration in a special organization, the best candidates are selected using the belief propagation algorithm. Next, this candidate configuration is combined with the current configuration using binary graph cuts as presented in the original version of the MBC algorithm. We tested the performance of our algorithm on the particular problem of counting flamingos in a colony, and show that it is much faster with the modified birth step.
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Communication dans un congrès
ICIP 2011 (International Conference on Image Processing), Sep 2011, Bruxelles, Belgium. 2011
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https://hal.inria.fr/inria-00592446
Contributeur : Ahmed Gamal Eldin <>
Soumis le : jeudi 12 mai 2011 - 15:13:08
Dernière modification le : mardi 13 septembre 2016 - 01:04:40
Document(s) archivé(s) le : vendredi 9 novembre 2012 - 11:15:45

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Ahmed Gamal Eldin, Xavier Descombes, Guillaume Charpiat, Josiane Zerubia. A fast multiple birth and cut algorithm using belief propagation. ICIP 2011 (International Conference on Image Processing), Sep 2011, Bruxelles, Belgium. 2011. <inria-00592446>

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