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Enhanced light field depth estimation for complex occlusion scenes
Author(s): Ying Jia; Weihai Li
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Paper Abstract

Depth estimation is always a hot topic in computer vision, which shows new vitality with the rise of light field camera. Nevertheless, occlusion is a tough problem, which degrades the precision of the acquired depth map. Although previous works have proposed some effective methods to solve this problem, regrettably they are deficient. In this paper, we extend previous single occlusion model into complex occlusion condition, adopt optical flow algorithm to get candidate occlusion points, combine multiple features to separate the angular patch, and employ more reasonable data cost to get the depth map. Because the proposed algorithm is more suitable for light field data, experimental results show that the proposed algorithm has a better performance than state-of-the-art algorithms on synthetic datasets and real world images captured by light field camera, especially for complex occlusion scenes.

Paper Details

Date Published: 9 August 2018
PDF: 6 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080669 (9 August 2018); doi: 10.1117/12.2503005
Show Author Affiliations
Ying Jia, Univ. of Science and Technology of China (China)
Weihai Li, Univ. of Science and Technology of China (China)

Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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