Stereo-matching algorithm based on energy minimization principle in Markov random field model

Tsuneo Saito; Hiroyuki Kudo; Taizo Anan; Chiho Iganami

doi:10.1117/12.253439

8 October 1996 Stereo-matching algorithm based on energy minimization principle in Markov random field model

Tsuneo Saito, Hiroyuki Kudo, Taizo Anan, Chiho Iganami

Proceedings Volume 2823, Statistical and Stochastic Methods for Image Processing; (1996) https://doi.org/10.1117/12.253439
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

In this paper, we develop anew intensity-based stereo matching algorithm using maximum a posteriori estimation based on the framework of Markov random field. The intensity-based stereo matching process is formulated as a problem to search for the minimum cost energy function which maximizes the a posteriori probability. We introduce an objective cost function called energy function of piecewise smooth disparity field, in which the discontinuities and occlusions are explicitly taken into account. In order to minimize the non-convex energy function for disparity estimation, we propose a relaxation algorithm called mean field annealing which provides results nearly as good as simulated annealing but with much faster convergence. Unlike the conventional correlation matching or feature matching, the proposed method provides a dense array of disparities, eliminating the need of interpolation for the 3D structure reconstruction. Several experimental results with synthetic and real stereo images are presented to evaluate the performance s of proposed algorithm.

Citation Download Citation

Tsuneo Saito, Hiroyuki Kudo, Taizo Anan, and Chiho Iganami "Stereo-matching algorithm based on energy minimization principle in Markov random field model", Proc. SPIE 2823, Statistical and Stochastic Methods for Image Processing, (8 October 1996); https://doi.org/10.1117/12.253439

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