Abstract:The paper presents a new method of depth estimation dedicated for free-viewpoint television (FTV). The estimation is performed for segments and thus their size can be used to control a trade-off between the quality of depth maps and the processing time of their estimation. The proposed algorithm can take as its input multiple arbitrarily positioned views which are simultaneously used to produce multiple inter view consistent output depth maps. The presented depth estimation method uses novel parallelization and temporal consistency enhancement methods that significantly reduce the processing time of depth estimation. An experimental assessment of the proposals has been performed, based on the analysis of virtual view quality in FTV. The results show that the proposed method provides an improvement of the depth map quality over the state of-the-art method, simultaneously reducing the complexity of depth estimation. The consistency of depth maps, which is crucial for the quality of the synthesized video and thus the quality of experience of navigating through a 3D scene, is also vastly improved.
Abstract:The paper presents a novel approach to 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 Cut similarity metric is constantly updated so that only non-occluded fragments in side views are considered. At each iteration of the algorithm non-occluded fragments are detected based on side view virtual depth maps synthesized from the best currently estimated depth map of the center view. Then 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, have proved that the depth maps estimated with the proposed approach provide about 1.25 dB virtual view quality improvement in comparison to the virtual view synthesized based on depth maps generated by the state-of-the-art MPEG Depth Estimation Reference Software.