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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Feng Zou Dong Tian Vetro, A. Ortega, A. |
| Copyright Year | 2013 |
| Description | Author affiliation: Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA (Ortega, A.) || Mitsubishi Electr. Res. Labs., Cambridge, MA, USA (Feng Zou; Dong Tian; Vetro, A.) |
| Abstract | Advanced multiview video systems are able to generate intermediate viewpoints of a 3D scene. In addition to the texture content, corresponding depth is associated with each viewpoint. To improve the coding efficiency of such content, view synthesis prediction can be used to further reduce inter-view redundancy in addition to traditional disparity compensated prediction. However, the predictor generated from the view synthesis process is affected by several factors, including signal properties of the texture, the accuracy of the depth and complexity of the scene, as well as coding errors in both the texture and depth. This paper presents an analysis of view synthesis prediction performance considering these factors. Based on this analysis, an adaptive depth quantization scheme is proposed to improve the depth coding, leading to better view synthesis prediction and overall coding efficiency gains. The proposed scheme is able to achieve an average bit rate savings of 0.9% on the coded and synthesized video with a maximum gain of up to 11.7% on the dependent views in the context of an HEVC-based codec. |
| Starting Page | 1694 |
| Ending Page | 1698 |
| File Size | 189440 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479923410 |
| DOI | 10.1109/ICIP.2013.6738349 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-09-15 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | multiview View synthesis prediction depth coding adaptive quantization |
| Content Type | Text |
| Resource Type | Article |
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