| Abstract |
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A novel region-based progressive stereo matching algorithm is presented. It combines the strengthes of previous region-based and progressive approaches. The progressive framework avoids the time consuming global optimization, while the inherent problem, the sensitivity to early wrong decisions, is significantly alleviated via the region-based representation. A growing-like process matches the regions progressively using a global best-first strategy based on a cost function integrating disparity smoothness and visibility constraint. The performance on standard evaluation platform using various real images shows that the algorithm is among the state-of-the-art both in accuracy and efficiency.
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 Additional Information
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Citation:
Yichen Wei, Long Quan,
"Region-Based Progressive Stereo Matching,"
cvpr,
pp. 106-113,
2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'04) - Volume 1,
2004
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