Fast disparity estimation for multi-view plus depth video coding

Abstract

Disparity estimation is used in Multi-view Video Coding (MVC) to remove the inter-view redundancies present in both color and depth multi-view video sequences. The standard H.264/MVC achieves high compression efficiency by deriving the optimal disparity vector through the exhaustive calculation of the Rate-Distortion cost function for all the possible search points. This makes disparity estimation highly computational expensive. This paper proposes an efficient technique that exploits both the multi-view and the epipolar geometries to determine the optimal search area, resulting in a reduction of search points and thus computations. Simulation results show that this technique can save up to 95% of the computational cost for disparity estimation, with negligible loss in coding efficiency for both the color and the depth multi-view video coding.