Segment-wise prediction in 3D video coding

3D video is an emerging technology that bundles depth information with texture videos to allow for view synthesis applications at the receiver. Depth discontinuities define object boundaries in both, depth maps and the collocated texture video. Therefore, depth segmentation can be utilized for a fine-grained motion field segmentation of the corresponding texture component. In this paper, depth information is used to increase coding efficiency for texture videos by deriving an arbitrarily shaped segmentation mask. By applying independent motion compensation to each of these segments and subsequently merging the two prediction signals, a highly accurate prediction signal can be generated that reduces the energy in the remaining texture residual signal. Simulation results show bitrate savings of up to 2.8% for the dependent texture views and up to about 1.0% with respect to the total bitrate.