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Proceedings Paper

Stereo matching using neighboring system constructed with MST
Author(s): Ran Li; Zhiguo Cao; Qian Zhang; Yang Xiao; Ke Xian
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Paper Abstract

Stereo matching is a hot topic in computer vision, while stereo matching in large textureless regions and slanted planes are still challenging problems. We propose a novel stereo matching algorithm to handle the problems. We novelly utilizes minimum spanning tree (MST) to construct a new superpixel-based neighboring system. The neighboring system is used to improve the matching performance in textureless regions. Then we apply the new neighboring system to the stereo matching problem, which uses the superpixel as the matching primitive. The use of the new neighboring system is efficient and effective. We compare our method with 4 popular methods. Experiments on Middlebury dataset show that our method can achieve good matching results. Especially, our method obtains more accurate disparity in textureless regions while maintaining a comparable performance of matching in slanted planes.

Paper Details

Date Published: 26 June 2017
PDF: 8 pages
Proc. SPIE 10334, Automated Visual Inspection and Machine Vision II, 103340F (26 June 2017); doi: 10.1117/12.2269385
Show Author Affiliations
Ran Li, Huazhong Univ. of Science and Technology (China)
Zhiguo Cao, Huazhong Univ. of Science and Technology (China)
Qian Zhang, Hubei Univ. (China)
Yang Xiao, Huazhong Univ. of Science and Technology (China)
Ke Xian, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 10334:
Automated Visual Inspection and Machine Vision II
Jürgen Beyerer; Fernando Puente León, Editor(s)

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