In this paper, we propose a novel binary-based cost computation and aggregation approach for stereo matching problem. The cost volume is constructed through bitwise operations on a series of binary strings. Then this approach is combined with traditional winner-take-all strategy, resulting in a new local stereo matching algorithm called binary stereo matching (BSM). Since core algorithm of BSM is based on binary and integer computations, it has a higher computational efficiency than previous methods. Experimental results on Middlebury benchmark show that BSM has comparable performance with state-of-the-art local stereo methods in terms of both quality and speed. Furthermore, experiments on images with radiometric differences demonstrate that BSM is more robust than previous methods under these changes, which is common under real illumination.
@article{arxiv.1402.2020,
title = {Binary Stereo Matching},
author = {Kang Zhang and Jiyang Li and Yijing Li and Weidong Hu and Lifeng Sun and Shiqiang Yang},
journal= {arXiv preprint arXiv:1402.2020},
year = {2014}
}
Comments
Pattern Recognition (ICPR), 2012 21st International Conference on