Local stereo matching algorithm using rotation-skeleton-based region

Abstract

This paper proposes a local stereo matching algorithm for accurate disparity estimation by using 45° rotation-skeleton-based region (RSBR). For local stereo matching, an adaptive local region is important for the performance of the disparity estimation. In order to generate more accurate regions, we use a skeleton with 45° rotation to divide an initial window that achieved by mean-shift segmentation into four parts. All the pixels in the same height level are judged simultaneously, and the valid pixels in the four parts construct the 45° RSBR. Compared with the common local support region based on orthogonal skeleton, 45° RSBR enables to maintain the consistency in images and have the advantage of error tolerance. The local stereo matching algorithm with RSBR is improved in two aspects. First, the hybrid cost aggregation using the RSBR helps to remove some noise caused by outliers and improve the subjective performance. Second, the candidate values in the refinement step are selected from the RSBR, which ensures the validity of candidates. The experiment results demonstrate a good performance in Middlebury Stereo datasets, both in objective and subjective performance.