Reducing 3D video coding complexity through more efficient disparity estimation

3D video coding for transmission exploits the Disparity Estimation (DE) to remove the inter-view redundancies present within both the texture and the depth map multi-view videos. Good estimation accuracy can be achieved by partitioning the macro-block into smaller subblocks partitions. However, the DE process must be performed on each individual sub-block to determine the optimal mode and their disparity vectors, in terms of rate-distortion efficiency. This vector estimation process is heavy on computational resources, thus, the coding computational cost becomes proportional to the number of search points and the inter-view modes tested during the rate-distortion optimization. In this paper, a solution that exploits the available depth map data, together with the multi-view geometry, is proposed to identify a better DE search area; such that it allows a reduction in its search points. It also exploits the number of different depth levels present within the current macro-block to determine which modes can be used for DE to further reduce its computations. Simulation results demonstrate that this can save up to 95% of the encoding time, with little influence on the coding efficiency of the texture and the depth map multi-view video coding. This makes 3D video coding more practical for any consumer devices, which tend to have limited computational power.