Edge-aware dynamic programming-based cost aggregation for robust stereo matching

Song Zhu; Danhua Cao; Yubin Wu; Shixiong Jiang

doi:10.1117/1.JEI.24.4.043016

17 August 2015 Edge-aware dynamic programming-based cost aggregation for robust stereo matching

Song Zhu, Danhua Cao, Yubin Wu, Shixiong Jiang

Author Affiliations +

Journal of Electronic Imaging, Vol. 24, Issue 4, 043016 (August 2015). https://doi.org/10.1117/1.JEI.24.4.043016

Abstract

Binocular stereo matching is one of the core algorithms in stereo vision. The edge-aware filter-based cost aggregation methods can produce precise disparity maps on the famous Middlebury benchmark (indoor). However, they perform poorly on the KITTI vision benchmark (outdoor) because frontal-parallel surfaces are assumed in the filter-based methods. We propose a new cost aggregation algorithm which discards the frontal-parallel surfaces assumption. The proposed algorithm performs like optimizing an energy function via dynamic programming. The proposed energy function integrates the pairwise smooth energy by the edge-aware filtering approach, which makes the proposed method adapt to slanted surfaces. The proposed algorithm not only outperforms the edge-aware filter-based local methods on the Middlebury benchmark but also performs well on the KITTI vision benchmark.

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Song Zhu, Danhua Cao, Yubin Wu, and Shixiong Jiang "Edge-aware dynamic programming-based cost aggregation for robust stereo matching," Journal of Electronic Imaging 24(4), 043016 (17 August 2015). https://doi.org/10.1117/1.JEI.24.4.043016

Published: 17 August 2015

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