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- W3016048233 abstract "In this paper, a novel depth estimation algorithm tackling foreground occlusion is proposed based on the neighborhood distribution in the sheared epipolar images (EPIs). First, the EPI is sheared to perform refocusing. Next a series of sheared EPI's neighboring pixels in a local window are selected and the corresponding histogram distributions are analyzed by the proposed novel tensor, Kullback-Leibler Divergence (KLD). Then, depths calculated from vertical and horizontal EPIs' tensors are fused according to the tensors' variation scale for a high quality depth map. Finally, confident depth points are propagated to the whole image by global optimization. Experimental results show that the proposed algorithm achieves better performance relative to state-of-the-art algorithms." @default.
- W3016048233 created "2020-04-17" @default.
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- W3016048233 date "2020-05-01" @default.
- W3016048233 modified "2023-09-24" @default.
- W3016048233 title "EPI-Neighborhood Distribution Based Light Field Depth Estimation" @default.
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- W3016048233 doi "https://doi.org/10.1109/icassp40776.2020.9053664" @default.
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