Compression of the statistical redundancy among different viewpoints, i.e., inter-view redundancy, is a fundamental and critical problem in multiview and three-dimensional (3D) video coding. To exploit the inter-view redundancy, disparity vectors are required to identify pixels of the same objects within two different views; in this way, the enhancement coding tools can be efficiently employed as new modes in block-based video codecs to achieve higher compression efficiency. Although disparity can be converted from depth, it is not possible in multiview video coding since depth information is not considered. Even when depth information is coded, it breaks the so-called multiview compatibility wherein texture views can be decoded without depth information. To resolve this problem, in this paper, a neighboring block-based disparity vector derivation (NBDV) method is proposed. The basic concept of NBDV is to derive a disparity vector (DV) of a current block by utilizing the motion information of spatially and temporally neighboring blocks predicted from another view. Through extensive experiments and analysis, it is shown that the proposed NBDV method achieves efficient DV derivation in the state-of-art video codecs, and it keeps the multiview compatibility with a relatively lower complexity. The proposed method has become an essential part of the 3D video standard extensions of H.264/AVC and HEVC.

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viewpoints ie interview redundancy blockbased video codecs enhancement coding tools motion information neighboring blockbased disparity vector derivation nbdv method compression stateofart video codecs multiview and threedimensional 3d video coding the statistical redundancy neighboring blocks socalled multiview compatibility texture views

Y.Chen, J.W.Kang, L.Zhang, X.Zhao,.Multiview and 3D Video Compression Using Neighboring Block Based Disparity Vectors. (),576-589.

Y.Chen, et al."Multiview and 3D Video Compression Using Neighboring Block Based Disparity Vectors"

Y.Chen, J.W.Kang, L.Zhang, X.Zhao,"Multiview and 3D Video Compression Using Neighboring Block Based Disparity Vectors"