Occlusion is one of the most challenging problems in depth estimation. Previous work has modeled the single-occluder occlusion in light field and get good results, however it is still difficult to obtain accurate depth for multi-occluder occlusion. In this paper, we explore the multi-occluder occlusion model in light field, and derive the occluder-consistency between the spatial and angular space which is used as a guidance to select the un-occluded views for each candidate occlusion point. Then an anti-occlusion energy function is built to regularize depth map. The experimental results on public light field datasets have demonstrated the advantages of the proposed algorithm compared with other state-of-the-art light field depth estimation algorithms, especially in multi-occluder areas.
@article{arxiv.1608.04187,
title = {Occlusion-Model Guided Anti-Occlusion Depth Estimation in Light Field},
author = {Hao Zhu and Qing Wang and Jingyi Yu},
journal= {arXiv preprint arXiv:1608.04187},
year = {2017}
}