Efficient Stereo Matching with Decoupled Dissimilarity Measure Using Successive Weighted Summation

Mathematical Problems in Engineering. 2014;2014 DOI 10.1155/2014/127284

 

Journal Homepage

Journal Title: Mathematical Problems in Engineering

ISSN: 1024-123X (Print); 1563-5147 (Online)

Publisher: Hindawi Limited

LCC Subject Category: Technology: Engineering (General). Civil engineering (General) | Science: Mathematics

Country of publisher: United Kingdom

Language of fulltext: English

Full-text formats available: PDF, HTML, ePUB, XML

 

AUTHORS


Cheng-Tao Zhu (School of Electronic Information Engineering, TianJin University, TianJin 300072, China)

Yau-Zen Chang (Department of Mechanical Engineering, Chang Gung University, Taoyuan 33302, Taiwan)

Huai-Ming Wang (Department of Mechanical Engineering, Chang Gung University, Taoyuan 33302, Taiwan)

Kai He (School of Electronic Information Engineering, TianJin University, TianJin 300072, China)

Shih-Tseng Lee (Department of Neurosurgery, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan)

Chung-Fu Lee (Department of Mechanical Engineering, Chang Gung University, Taoyuan 33302, Taiwan)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 26 weeks

 

Abstract | Full Text

Developing matching algorithms from stereo image pairs to obtain correct disparity maps for 3D reconstruction has been the focus of intensive research. A constant computational complexity algorithm to calculate dissimilarity aggregation in assessing disparity based on separable successive weighted summation (SWS) among horizontal and vertical directions was proposed but still not satisfactory. This paper presents a novel method which enables decoupled dissimilarity measure in the aggregation, further improving the accuracy and robustness of stereo correspondence. The aggregated cost is also used to refine disparities based on a local curve-fitting procedure. According to our experimental results on Middlebury benchmark evaluation, the proposed approach has comparable performance when compared with the selected state-of-the-art algorithms and has the lowest mismatch rate. Besides, the refinement procedure is shown to be capable of preserving object boundaries and depth discontinuities while smoothing out disparity maps.