KEYWORDS: Video, Video coding, Video compression, 3D video compression, Motion estimation, Cameras, Distortion, Independent component analysis, Data compression, Signal processing
Nowadays, the 3D video system using the MVD (multi-view video plus depth) data format is being actively studied. The
system has many advantages with respect to virtual view synthesis such as an auto-stereoscopic functionality, but
compression of huge input data remains a problem. Therefore, efficient 3D data compression is extremely important in
the system, and problems of low temporal consistency and viewpoint correlation should be resolved for efficient depth
video coding. In this paper, we propose an object-adaptive depth compensated inter prediction method to resolve the
problems where object-adaptive mean-depth difference between a current block, to be coded, and a reference block are
compensated during inter prediction. In addition, unique properties of depth video are exploited to reduce side
information required for signaling decoder to conduct the same process. To evaluate the coding performance, we have
implemented the proposed method into MVC (multiview video coding) reference software, JMVC 8.2. Experimental
results have demonstrated that our proposed method is especially efficient for depth videos estimated by DERS (depth
estimation reference software) discussed in the MPEG 3DV coding group. The coding gain was up to 11.69% bit-saving,
and it was even increased when we evaluated it on synthesized views of virtual viewpoints.
KEYWORDS: Video, Video coding, Video compression, 3D video compression, Signal to noise ratio, Computer programming, Electronics, Video processing, Edge detection, Quantization
In 3D video system including depth information, once a depth video is coded by the state-of-the-art video compression
tools such as H.264/AVC, depth errors around the boundaries of objects can be intensified, and these can significantly
affect the quality of rendered virtual view later. Despite this drawback of depth video coding, its compression is essential
because of the enormous amount of input data in 3D video system. In this paper, we propose a line-based partitioned
intra prediction method which exploits geometric redundancy of depth video for an efficient compression without
significant errors around boundaries. The proposed algorithm can efficiently divide the current coded block into two
partitioned regions, and the algorithm independently predicts each region with previously coded neighbor pixel
information. Finally, the generated prediction mode adaptively alternates the conventional DC intra prediction mode. To
evaluate the intra prediction performances, we have implemented the proposed method into H.264/AVC intra prediction
scheme. Experimental results have demonstrated that our proposed method provides higher coding performance. The
coding performance for depth video compression itself was up to 3.71% bit-saving or 0.309dB on maximum peak signalto-
noise ratio (PSNR) gain among proper depth sequences which contain line-like boundaries.
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