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Proceedings Article

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

[+] Author Affiliations
Yi Peng, Ge Li, Ronggang Wang, Wenmin Wang

Peking Univ. (China)

Proc. SPIE 9393, Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015, 939309 (March 17, 2015); doi:10.1117/12.2083741
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From Conference Volume 9393

  • Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015
  • Robert Sitnik; William Puech
  • San Francisco, California, United States | February 08, 2015

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. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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 (March 17, 2015); doi:10.1117/12.2083741; http://dx.doi.org/10.1117/12.2083741


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