  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.
