Integration of optical flow and Multi-Path-Viterbi algorithm for stereo vision

This paper proposes a novel stereo matching algorithm to solve environment sensing problems. It integrates a non-convex optical flow and Viterbi process. The non-convex optical flow employs a new adaptive weighted non-convex Total Generalized Variation (TGV) model, which can obtain sharp disparity maps. Structural similarity, total variation constraint, and a specific merging strategy are combined with the 4 bi-directional Viterbi process to improve the robustness. In the fusion of the optical flow and Viterbi process, a new occlusion processing method is incorporated in order to get more sharp disparity and more robust result. Extensive experiments are conducted to compare this algorithm with other state-of-the-art methods. Experimental results show the superiority of our algorithm.