Adaptive Motion Vector Prediction for Omnidirectional Video

Abstract

Omnidirectional video is widely used in virtual reality applications in order to create the immersive experience to the user. Such content is projected onto a 2D image plane in order to make it suitable for compression purposes by using current standard codecs. However, the resulted projected video contains deformations mainly due to the oversampling of the projection plane. These deformations are not favorable for the motion models that are used in the recent video compression standards. Hence, omnidirectional video is not efficiently compressible with the current codecs. In this work, an adaptive motion vector prediction method is proposed for efficiently coding the motion information of such content. The proposed method adaptively models the motion vectors of the coding block based on the motion information of the neighboring blocks and calculates a more optimal motion vector predictor for coding the motion information. The experimented results showed that the proposed motion vector prediction method provides up to 2.2% bitrate reduction in the content with high motion and on average 1.1% bitrate reduction for the tested sequences.