Occlusion Handling by Successively Excluding Foregrounds for Light Field Depth Estimation Based on Foreground-Background Separation

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This paper proposes a depth from light field (DFLF) method specifically to deal with occlusion based on the foreground-background separation (FBS). The FBS-based methods infer the disparity maps by accumulating the binary maps which divide whether each pixel is the foreground or background. Although there have been widely studied to handle the occlusion problem with the cost-based method, there are not enough researches to handle the occlusion problem with the FBS-based methods yet. We found that errors around the occlusion boundary in the resulting disparity maps of the FBS-based methods arise from the fattened foreground by the light field reprameterization. To avoid fattened foregrounds, the inferred foreground maps in the front region with respect to the disparity axis could be utilized in the back region in the three-dimensional volume construction, which corresponds to the cost volume construction in the cost-based methods. With the front-to-back scanning manner of the FBS-based method, by successively excluding inferred foreground maps, errors around occlusion boundary could be effectively reduced in the resulting disparity maps. With synthetic and real LF images, the proposed method shows reasonable performance compared to the existing methods and better performance than existing FBS-based methods. © 2013 IEEE.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2021-07
Language
English
Article Type
Article
Citation

IEEE ACCESS, v.9, pp.103927 - 103936

ISSN
2169-3536
DOI
10.1109/ACCESS.2021.3098819
URI
http://hdl.handle.net/10203/291126
Appears in Collection
EE-Journal Papers(저널논문)
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