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Proceedings Paper

Stereo matching with space-constrained cost aggregation and segmentation-based disparity refinement
Author(s): Yi Peng; Ge Li; Ronggang Wang; Wenmin Wang
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Paper Abstract

Stereo matching is a fundamental topic in computer vision. Usually, stereo matching is mainly composed of four stages: cost computation, cost aggregation, disparity optimization and disparity refinement. In this paper, we propose a novel stereo matching method with space-constrained cost aggregation and segmentation-based disparity refinement. Stateof- the-art methods are used for cost aggregation and disparity optimization stages. Three technical contributions are given in this paper. First, applying space-constrained cross-region in cost aggregation stage; second, utilizing both color and disparity information in image segmentation; third, using image segmentation and occlusion region detection to aid disparity refinement. The performance of our platform ranks second in the Middlebury evaluation.

Paper Details

Date Published: 17 March 2015
PDF: 11 pages
Proc. SPIE 9393, Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015, 939309 (17 March 2015); doi: 10.1117/12.2083741
Show Author Affiliations
Yi Peng, Peking Univ. (China)
Ge Li, Peking Univ. (China)
Ronggang Wang, Peking Univ. (China)
Wenmin Wang, Peking Univ. (China)


Published in SPIE Proceedings Vol. 9393:
Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015
Robert Sitnik; William Puech, Editor(s)

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