Stereo matching using neighboring system constructed with MST

Ran Li; Zhiguo Cao; Qian Zhang; Yang Xiao; Ke Xian

doi:10.1117/12.2269385

26 June 2017 Stereo matching using neighboring system constructed with MST

Ran Li; Zhiguo Cao; Qian Zhang; Yang Xiao; Ke Xian;

Author Affiliations +

Proceedings Volume 10334, Automated Visual Inspection and Machine Vision II; 103340F (2017) https://doi.org/10.1117/12.2269385
Event: SPIE Optical Metrology, 2017, Munich, Germany

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.

Citation Download Citation

Ran Li, Zhiguo Cao, Qian Zhang, Yang Xiao, Ke Xian, "Stereo matching using neighboring system constructed with MST", Proc. SPIE 10334, Automated Visual Inspection and Machine Vision II, 103340F (26 June 2017); doi: 10.1117/12.2269385; https://doi.org/10.1117/12.2269385

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $14.40

Non-members: $18.00 ADD TO CART

Show All Keywords

Keywords/Phrases

Search In:

Publication Years