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Distributed Local Search for Elastic Image Matching

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Book cover Swarm Intelligence Based Optimization (ICSIBO 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10103))

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Abstract

We propose a distributed local search (DLS) algorithm, which is a parallel formulation of a local search procedure in an attempt to follow the spirit of standard local search metaheuristics. Applications of different operators for solution diversification are possible in a similar way to variable neighborhood search. We formulate a general energy function to be equivalent to elastic image matching problems. A specific example application is stereo matching. Experimental results show that the GPU implementation of DLS seems to be the only method that provides an increasing acceleration factor as the instance size augments, among eight tested energy minimization algorithms.

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Notes

  1. 1.

    For all the tested energy minimization algorithms, we use the original codes from http://vision.middlebury.edu/MRF/code/ .

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Authors and Affiliations

  1. IRTES-SeT, Université de Technologie de Belfort-Montbéliard, 90010, Belfort, France

    Hongjian Wang, Abdelkhalek Mansouri, Jean-Charles Créput & Yassine Ruichek

Authors
  1. Hongjian Wang
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  2. Abdelkhalek Mansouri
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  3. Jean-Charles Créput
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  4. Yassine Ruichek
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Corresponding author

Correspondence to Hongjian Wang .

Editor information

Editors and Affiliations

  1. Université Paris-Est Créteil, Vitry-sur-Seine, France

    Patrick Siarry

  2. LMIA-INRIA Grand Est, Université de Haute-Alsace, Mulhouse, France

    Lhassane Idoumghar

  3. Université de Haute-Alsace, Mulhouse, France

    Julien Lepagnot

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Wang, H., Mansouri, A., Créput, JC., Ruichek, Y. (2016). Distributed Local Search for Elastic Image Matching. In: Siarry, P., Idoumghar, L., Lepagnot, J. (eds) Swarm Intelligence Based Optimization. ICSIBO 2016. Lecture Notes in Computer Science(), vol 10103. Springer, Cham. https://doi.org/10.1007/978-3-319-50307-3_5

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  • DOI: https://doi.org/10.1007/978-3-319-50307-3_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50306-6

  • Online ISBN: 978-3-319-50307-3

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