Fast Stereo Matching Fully Utilizing Super-Pixels

Abstract

In this paper, we propose a depth image generation method by stereo matching on super-pixel (SP) basis. In the proposed method, block matching is performed only at the center of the SP, and the obtained disparity is applied to all pixels of the SP. Next, in order to improve the disparity, a new SP-based cost filter is introduced. This filter multiplies the matching cost of the surrounding SP by a weight based on reliability and similarity and sums the weighted costs of neighbors. In addition, we propose two new error checking methods. One-way check uses only a unidirectional disparity estimation with a small amount of calculation to detect errors. Cross recovery uses cross checking and error recovery to repair lacks of objects that are problematic with SP-based matching. As a result of the experiment, the execution time of the proposed method using the one-way check was about 1/100 of the full search, and the accuracy was almost equivalent. The accuracy using cross recovery exceeded the full search, and the execution time was about 1/60. Speeding up while maintaining accuracy increases the application range of depth images.