Stereo Matching via Disparity Estimation and Surface Modeling
Jong Dae Oh, Siwei Ma, C.‐C. Jay Kuo · 2007
Two new techniques are proposed to improve stereo matching performance in this work. First, to address the disparity discontinuity problem in occluded regions, we present a disparity estimation procedure, which consists of two steps; namely, a greedy disparity filling algorithm and a least-squared-errors (LSE) fitting method. Second, it is observed that the existing fronto-parallel model with color segmentation is built upon the piecewise constant surface approximation, which is however not efficient in approximating slanted or curved objects. We use a piecewise linear surface model to represent 3-dimensional (3D) geometric structure for better surface modeling. The proposed stereo matching system with these two new components is evaluated with Middlebury data sets with excellent quantitative and qualitative results.