Stereo matching with space-constrained cost aggregation and segmentation-based disparity refinement

Yi Peng; Ge Li; Ronggang Wang; Wenmin Wang

doi:10.1117/12.2083741

17 March 2015 Stereo matching with space-constrained cost aggregation and segmentation-based disparity refinement

Yi Peng, Ge Li, Ronggang Wang, Wenmin Wang

Proceedings Volume 9393, Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015; 939309 (2015) https://doi.org/10.1117/12.2083741
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

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.

Citation Download Citation

Yi Peng, Ge Li, Ronggang Wang, and Wenmin Wang "Stereo matching with space-constrained cost aggregation and segmentation-based disparity refinement", Proc. SPIE 9393, Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015, 939309 (17 March 2015); https://doi.org/10.1117/12.2083741

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