Panoramic Video Coding Using Affine Motion Compensated Prediction

This paper proposes an affine motion compensated prediction (AMCP) method to predict the complex changes between the successive frames in panoramic video coding. A panoramic video is an image-based rendering (IBR) technique [1] 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 and rotation etc. However, the traditional motion compensated prediction is a translational motion compensated prediction (TMCP) which cannot predict non-translational changes between panoramic images accurately. The AMCP can model the nontranslational motion effects of panoramic video accurately by using six motion coefficients which are estimated by Gauss Newton iterative minimization algorithm [2]. Simulated results show that the gain of coding performance is up to about 1.3 dB when using AMCP compared with TMCP in panoramic video coding.