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- W4320802924 abstract "Depth estimation is essential in many light field applications. In this paper, we present a depth estimation method from epipolar plane images(EPIs) by combining both linear consistency cue and regional distribution difference cue to improve the occlusion handling capability. For the linear consistency cue, a rotational linear entropy (RLE) metric is proposed to measure the pixel color consistency of an EPI line. For the distribution difference cue, a height-variable SPO (HSPO) that integrates the color consistency constraint as a new weight in SPO, is introduced to measure distribution difference. Integrating the two data costs is shown more robust to complex occlusions and varying planes. Cost volume filtering and global optimization are applied to improve the accurate of the final depth map. The experimental results demonstrate that the proposed method outperforms other state-of-art light field depth estimation methods in both qualitative and quantitative evaluations." @default.
- W4320802924 created "2023-02-15" @default.
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- W4320802924 date "2022-08-15" @default.
- W4320802924 modified "2023-09-26" @default.
- W4320802924 title "Multi-Cue Depth Estimation from Epipolar Plane Image" @default.
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- W4320802924 doi "https://doi.org/10.1109/ccdc55256.2022.10034099" @default.
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