Symmetric Pixel-Group Based Stereo Matching for Occlusion Handling
In this paper, we propose a symmetric pixel-group stereo model for handling occlusion in a segment-based style. Firstly, both images are segmented based on color, disparity, and the segments of the other image sequencely. Then the uniqueness constraint is embodied in pixel-group level. Finally, a sy...
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| creator | Xiuzhi Zhou Runsheng Wang |
| description | In this paper, we propose a symmetric pixel-group stereo model for handling occlusion in a segment-based style. Firstly, both images are segmented based on color, disparity, and the segments of the other image sequencely. Then the uniqueness constraint is embodied in pixel-group level. Finally, a symmetric belief propagation (BP) optimization framework is used to find correspondence and occlusions simultaneously. Results obtained for benchmark indicate that the proposed method is able to compete with the state-of-the-art algorithms. |
| doi_str_mv | 10.1109/ICPR.2006.1100 |
| format | Conference Proceeding |
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| issn | 1051-4651 |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Application software Belief propagation Computer vision Image segmentation Iterative algorithms Layout Minimization methods Optimization methods Pixel Stereo vision |
| title | Symmetric Pixel-Group Based Stereo Matching for Occlusion Handling |
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