Stripe mesh based disparity estimation by using 3-D Hough transform

This correspondence presents a novel matching technique for disparity estimation. The technique combines advantages of an adaptive stripe-based mesh structure and Hough transform. First, a mesh that is composed of triangular patches and fits to the depth changes is generated by using edge maps. In each patch, the depth of the scene is approximated by a surface. A search space is built by difference maps that are obtained by subtracting the left image from the shifted versions of the right image. From the search space, 3-D Hough spaces are produced such that a point of the Hough space represents a surface in the search space. Then, a matching algorithm finds the combination of surfaces that gives minimum matching error in a neighborhood around patches by using Hough spaces. Continuity and smoothness constraints are formulated as probability density functions that modify the Hough spaces of the following patches by using the estimated surfaces for the previous ones. Our experiments demonstrate the accuracy of the proposed method