Depth estimation using modified cost function for occlusion handling

Abstract

This paper presents a novel approach to the occlusion handling problem in depth estimation using three views. A solution based on modification of similarity cost function is proposed. During the depth estimation via optimization algorithms, like Graph Cuts, the similarity metric is constantly updated so that only non-occluded fragments in the side views are considered. At each iteration of the algorithm, non-occluded fragments are detected based on side view virtual depth maps synthesized from currently the best estimated depth map of the center view. Then, the similarity metric is updated for correspondence search only in non-occluded regions of the side views. The experimental results, conducted on well-known 3D video test sequences, show that the depth maps estimated with the proposed approach provide about 1.25 dB virtual view quality improvement in comparison with the virtual view synthesized based on depth maps generated with the use of the state-of-the-art MPEG Depth Estimation Reference Software.