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IJCV
2008

Stereo Matching Using Population-Based MCMC

14 years 8 months ago
Stereo Matching Using Population-Based MCMC
In this paper, we propose a new stereo matching method using the population-based Markov Chain Monte Carlo (Pop-MCMC), which belongs to the sampling-based methods. Since the previous MCMC methods produce only one sample at a time, only local moves are available. In contrast, the proposed Pop-MCMC uses multiple chains in parallel and produces multiple samples at a time. It thereby enables global moves by exchanging information between samples, which in turn, leads to faster mixing rate. In the view of optimization, it means that we can reach a lower energy state rapidly. In order to apply Pop-MCMC to the stereo matching problem, we design two effective 2-D mutation and crossover moves among multiple chains to explore a high dimensional state space efficiently. The experimental results on real stereo images demonstrate that the proposed algorithm gives much faster convergence rate than conventional sampling-based methods including SA (Simulated Annealing) and SWC (Swendsen-Wang Cuts). An...
Wonsik Kim (Seoul National University), Joonyoung
Added 26 Jul 2009
Updated 02 Apr 2010
Type Journal
Year 2008
Where IJCV
Authors Wonsik Kim (Seoul National University), Joonyoung Park (Seoul National University), Kyoung Mu Lee (Seoul National University)
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