17 August 2015 Edge-aware dynamic programming-based cost aggregation for robust stereo matching
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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.
© 2015 SPIE and IS&T
Song Zhu, Song Zhu, Danhua Cao, Danhua Cao, Yubin Wu, Yubin Wu, Shixiong Jiang, 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 . Submission:

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