Stereo Matching Using Population-Based MCMC

  • Joonyoung Park
  • Wonsik Kim
  • Kyoung Mu Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4844)


In this paper, we propose a new stereo matching method using the population-based Markov Chain Monte Carlo (Pop-MCMC). Pop-MCMC belongs to the sampling-based methods. Since previous MCMC methods produce only one sample at a time, only local moves are available. However, since Pop-MCMC uses multiple chains and produces multiple samples at a time, it enables global moves by exchanging information between samples, and in turn leads to faster mixing rate. In the view of optimization, it means that we can reach a state with the lower energy. The experimental results on real stereo images demonstrate that the performance of proposed algorithm is superior to those of previous algorithms.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Joonyoung Park
    • 1
  • Wonsik Kim
    • 2
  • Kyoung Mu Lee
    • 2
  1. 1.DM research Lab., LG Electronics Inc., 16 Woomyeon-Dong, Seocho-Gu, 137-724, SeoulKorea
  2. 2.School of EECS, ASRI, Seoul National University, 151-742, SeoulKorea

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