Title | ||
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Cost-volume filtering-based stereo matching with improved matching cost and secondary refinement |
Abstract | ||
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Recent cost-volume filtering-based local stereo methods have achieved comparable accuracy with global methods. However, there are still some significant outliers existing in the final disparity map. In this paper, we propose a cost-volume filtering-based local stereo matching method that employs a new combined cost and a novel secondary disparity refinement mechanism. The combined cost is formulated by a modified color census transform, truncated absolute differences of color and gradients. Symmetric guided filter is used for the cost aggregation. Different from traditional stereo matching, a novel secondary disparity refinement is proposed to further remove remaining outliers. Experimental results on Mid-dlebury benchmark show that our method ranks the 5thout of the 144 submitted methods, and is the best cost-volume filtering-based local method. Furthermore, experiments on real world sequences also validate the effectiveness of our proposed method. © 2014 IEEE. |
Year | DOI | Venue |
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2014 | 10.1109/ICME.2014.6890201 | Proceedings - IEEE International Conference on Multimedia and Expo |
Keywords | Field | DocType |
Local stereo, cost-volume filtering, matching cost, disparity refinement | Local method,Stereo matching,Template matching,Computer vision,Pattern recognition,Computer science,Filter (signal processing),Outlier,Census transform,Artificial intelligence,Cost aggregation,Computer stereo vision | Conference |
Volume | Issue | ISSN |
2014-September | Septmber | 1945-7871 |
Citations | PageRank | References |
1 | 0.37 | 12 |
Authors | ||
6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jiao Jianbo | 1 | 63 | 9.88 |
Ronggang Wang | 2 | 134 | 36.57 |
Wang Wenmin | 3 | 88 | 19.53 |
Dong Shengfu | 4 | 8 | 2.92 |
Wang Zhenyu | 5 | 12 | 6.10 |
Wen Gao | 6 | 11374 | 741.77 |