Rotational Motion Compensated Prediction in HEVC Based Omnidirectional Video Coding

Abstract

Spherical video is becoming prevalent in virtual and augmented reality applications. With the increased field of view, spherical video needs enormous amounts of data, obviously demanding efficient compression. Existing approaches simply project the spherical content onto a plane to facilitate the use of standard video coders. Earlier work at UCSB was motivated by the realization that existing approaches are suboptimal due to warping introduced by the projection, yielding complex non-linear motion that is not captured by the simple translational motion model employed in standard coders. Moreover, motion vectors in the projected domain do not offer a physically meaningful model. The proposed remedy was to capture the motion directly on the sphere with a rotational motion model, in terms of sphere rotations along geodesics. The rotational motion model preserves the shape and size of objects on the sphere. This paper implements and tests the main ideas from the previous work [1] in the context of a full-fledged, unconstrained coder including, in particular, bi-prediction, multiple reference frames and motion vector refinement. Experimental results provide evidence for considerable gains over HEVC.