Occlusion Detection Using Warping and Cross- Checking Constraints for Stereo Matching

In this paper, we propose an occlusion detection algorithm which estimates occluded pixels automatically. In order to detect the occlusion, we obtain an initial disparity map with an optimization algorithm based on the modified constant-space belief propagation (CSBP) which has low complexity. The initial disparity map gives us clues for occlusion detection. These clues are the warping constraint and the cross check constraint. From both constraints, we define a potential energy function for occlusion detection and optimize it using an energy minimization framework. Experimental results show that the result of the occlusion detection from the proposed algorithm is very close to the ground truth.