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Real-Time Accurate Stereo Matching Using Modified Two-Pass Aggregation and Winner-Take-All Guided Dynamic Programming

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5 Author(s)
Xuefeng Chang ; State Key Lab. of Virtual Reality Technol. & Syst., Beihang Univ., Beijing, China ; Zhong Zhou ; Liang Wang ; Yingjie Shi
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This paper presents a real-time stereo algorithm that estimates scene depth information with high accuracy. Our algorithm consists of two novel components. First, we apply a modified two-pass aggregation to the adaptive cost aggregation process, use color similarity to calculate support weight, and introduce a credibility estimation mechanism to reduce accuracy loss during two-pass aggregation. Second, we present an amended scan-line optimization technique, which combines winner-take-all and dynamic programming. Our algorithm runs at 20 fps on 320×240 video with a disparity search range of 24. The experimental results are evaluated on the Middlebury benchmark data sets, showing that our method achieves the best reconstruction accuracy among all real-time stereo algorithms.

Published in:

3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2011 International Conference on

Date of Conference:

16-19 May 2011