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• W2037264549 abstract "In this study, a multi-scale phase based sparse disparity algorithm and a probabilistic model for matching uncertain phase are proposed. The features used are oriented edges extracted using steerable filters. Feature correspondences are estimated using phase-similarity at multiple scale using a magnitude weighting scheme. In order to achieve sub-pixel accuracy in disparity, we use a fine tuning procedure which employs the phase difference between corresponding feature points. We also derive a probabilistic model, where phase uncertainty is trained using data from a single image pair. The model is used to provide stable matches. The disparity algorithm and the probabilistic phase uncertainty model are verified on various stereo image pairs." @default.
• W2037264549 created "2016-06-24" @default.
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• W2037264549 date "2007-09-01" @default.
• W2037264549 modified "2023-09-26" @default.
• W2037264549 title "A statistical approach to sparse multi-scale phase-based stereo" @default.
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• W2037264549 doi "https://doi.org/10.1016/j.patcog.2006.10.019" @default.
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