Stereo matching based on segmented B-spline surface fitting and accelerated region belief propagation

Jingzhou Huang

Stereo matching based on segmented B-spline surface fitting and accelerated region belief propagation

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Author(s): Jingzhou Huang ¹
- Affiliations: 1: College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, People's Republic of China
Source: Volume 9, Issue 4, August 2015, p. 456 – 466
DOI: 10.1049/iet-cvi.2014.0166 , Print ISSN 1751-9632, Online ISSN 1751-9640

Received 23/06/2014, Accepted 20/11/2014, Revised 22/09/2014, Published 02/03/2015

The authors propose a new stereo matching algorithm based on an iterative optimisation framework including bi-cubic B-spline surface fitting and accelerated region belief propagation (BP). They first compute the initial cost and disparity map by the adaptive support-weight approach and then launch the iterative process in which the disparity space image is refined via the bi-cubic B-spline fitting and optimised via the accelerated region BP. Two innovations are contained in the algorithm: (i) disparity space image refinement based on segmented bi-cubic B-spline surface fitting; and (ii) an accelerated region message passing approach for BP. The algorithm is verified on the Middlebury benchmark and experimental results show the algorithm is effective and achieves the state-of-the-art accuracy.

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Stereo matching based on segmented B-spline surface fitting and accelerated region belief propagation

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