Adaptive Selection of Motion Models for Panoramic Video Coding

A panoramic video is an image-based rendering (IBR) technique which provides users with a large field of view (e.g. 360 degree) on surrounding dynamic scenes. It includes not only the translational motions but also the non-translational motions, such as zooming, rotation and uneven stretching etc. This paper presents a motion compensated prediction scheme based on adaptive selection of motion models to predict the complex changes between successive frames efficiently in panoramic video coding. By performing the initial motion estimation phrase and the refined motion estimation phrase in the proposed scheme, simulated results show that the coding performance of the proposed scheme is much higher than the traditional motion compensated prediction scheme in panoramic video coding.