• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Local Stereo Matching Using Combined Matching Cost and Adaptive Cost Aggregation

Vol. 9, No. 1, January 30, 2015
10.3837/tiis.2015.01.012, Download Paper (Free):

Abstract

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.


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Cite this article

[IEEE Style]
S. Zhu and Z. Li, "Local Stereo Matching Using Combined Matching Cost and Adaptive Cost Aggregation," KSII Transactions on Internet and Information Systems, vol. 9, no. 1, pp. 224-241, 2015. DOI: 10.3837/tiis.2015.01.012.

[ACM Style]
Shiping Zhu and Zheng Li. 2015. Local Stereo Matching Using Combined Matching Cost and Adaptive Cost Aggregation. KSII Transactions on Internet and Information Systems, 9, 1, (2015), 224-241. DOI: 10.3837/tiis.2015.01.012.