Qiuwen Zhang

Low complexity multiview video plus depth coding

Multiview video plus depth (MVD) is a new 3D video format that would support 3D applications developed by MPEG. Such a format is a combination of texture video and associated depth maps. Consequently, for the efficient transmission of 3D video signals, the compression of texture video and also the depth maps is required. Since high computational complexity of jointly coding between the texture video and depth map is still an open question, this paper introduces a low complexity MVD coding algorithm that adaptively utilizes the texture and depth map correlation. Based on the correlation, we propose four efficient techniques, including depth information based fast mode size decision, adaptive disparity estimation in texture coding, motion vector sharing based on the texture image similarity correlation and the SKIP mode decision in depth coding. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of MVD coding while improve the coding performance and achieve better rendering quality1.

Efficient rendering distortion estimation for depth map compression

A depth map represents three-dimensional (3D) scene information and is used to synthesize virtual views in 3D video. Since the quality of synthesized virtual views highly depends on the quality of depth map, efficient depth compression is crucial to realize the 3D video system. However compressing depth map using existing video coding techniques yields unacceptable distortions while rendering virtual views. To solve this problem, we propose an efficient depth map compression method for the view rendering, a novel distortion metric base on view rendering distortions instead of distortion of depth map itself. First, we derive relationships between distortions in coded depth map and rendered view. Then, a region based video characteristics distortion model is proposed for precisely estimation distortion in view synthesis. Finally, experimental results have shown that 1.8 dB coding gain in terms of PSNR and subjective quality improvement of synthesized views are achieved by the proposed method.

Reduced resolution depth compression for multiview video plus depth coding

Multiview video plus depth (MVD) is a new 3D video format that would support 3D video applications. The primary goals are the high-quality reconstruction of an arbitrary number of views for 3D television (3DTV) and free viewpoint television (FTV). Its quality depends highly on the quality of depth image, a depth compression base B-spline interpolation is proposed for MVD to improve the 3D video coding (3DVC). The depth map is down sampling prior to multiview video coding (MVC) encoding and up sampling after decoding. The results investigated by objective as well as subjective evaluations over several multi-view test sequences imply that the proposed methods reduce the bit-rate for depth coding and achieve better rendering quality.

An improved depth map estimation for coding and view synthesis

Inaccuracy depth estimation may influence on depth coding and virtual view rendering in the free-viewpoint television (FTV) system, an improved depth map estimation is proposed to solve the problem for coding and view synthesis. Firstly, check the consistency of initial depth, and the influence of initial miss-matches is minimized by introduction of an additional adaptive matching error selection that penalizes the unreliable matches. Then according to certain criteria, the multi-reference depth maps are merged into one disparity map to improve the quality of disparity map. Finally, a multilateral filtering is used to preserve details in the depth map and simultaneously smooth the depths in occluded areas at object boundary, less texture and discontinuity regions. Experimental results show a significant improvement of the initial input depth maps and coding efficiency, as well as a reduction of view synthesis artifacts.

Improved multi-view depth estimation for view synthesis in 3D video coding

Multi-view depth estimation is an important part in the virtual view synthesis and depth map coding within the 3DV/FTV applications. However, existing depth estimation methods generally have difficulty to generate good depth results around object edges or in areas with less texture. To solve this problem, we propose an improved algorithm to obtain a smooth and accurate depth map for view synthesis in 3D video coding. The proposed method aims to preserve details in the depth map and simultaneously smooth depths in object boundary occluded area, less texture and discontinuity regions, to avoid blurring in the synthesized views. Experimental results show a significant improvement of the initial input depth maps and coding efficiency, as well as a reduction of view synthesis artifacts.

New intermediate view synthesis method based on Tikhonov regularization

The intermediate view synthesis from arbitrary view is a challenging topic in multi-view areas, many image-based rendering methods have been proposed to solve this problem. A new multi-view intermediate view synthesis method based on Tikhonov regularization function is proposed to synthesis view from limited number of source views. The experiments show good results of the synthesized views.

A novel depth coding scheme for multiview video plus depth compression

Efficient compression of multi-view images and videos is an open and interesting research issue that has been attracting the attention of both academic and industrial world during the past several years. Multiview video plus depth (MVD) is a new 3D video format that would support 3D television (3DTV) and free viewpoint television (FTV). Depth-images are a 2D representation of the 3D scene surface and for 3DTV and FTV applications the depth information of MVD data is used for rendering virtual intermediate views of the scene. In this paper, we propose a novel coding scheme that is adapted to the special characteristics of depth-images, individual coding for color and depth data: the conventional multiview coding approach (MVC) is used for color videos and multidimensional multiscale parser (MMP) algorithm for depth maps coding. Experimental results show that the presented scheme achieves significant coding gains at high rate while compared with the joint multiview video model and Platelet depth coding.