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. !14
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