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Reliability-Based Discontinuity-Preserving Stereo Matching

In stereo matching, it is a challengeable task to effectively deal with occlusions between objects, which often cause disparity errors along object boundaries. In this paper, we propose discontinuity-preserving stereo matching based on reliability. We first estimate an initial disparity map by segmentation-based adaptive weights. Then, we obtain reliability for each pixel in an image, which indicates the correctness of the estimated disparity based on the matching cost. Finally, we minimize disparity errors caused by occlusions between objects using reliability and produce discontinuity-preserving disparity maps. Experiments on the Middlebury data set show that the proposed method successfully preserves disparity discontinuities along object boundaries and outperforms the state-of-the-art stereo matching methods.