A cost minimization with light field in scene depth MAP estimation
Yuchen Zhang, Hongkai Xiong · 2016
This paper proposes a scene depth map generation method based on lens-based light field cameras. In particular, it achieves the functions of the incident rays and the corresponding directional features, which can favor determining the coordinates of candidate space points. The light rays behind the aperture in the 4D light field would be converted into the rays before the aperture with their directions known. The light rays through the aperture center are denoted as reference light rays and keep their directions. With the probability (cost) of each reference light ray in each depth value, we obtain an initial depth map by selecting the depth value with minimum cost. It would be refined via multi-label optimization and weighted median filtering. Experimental results demonstrate the accuracy of the depth map estimated by the proposed method.