Affine Model Based Motion Compensation Prediction for Zoom

Zoom motion is classified into two categories, i.e., global zoom motion and local zoom motion. A simple affine motion model with four parameters is utilized to describe zoom motion efficiently based on the analyses of camera imaging principles. Based on the motion model, a basic candidate motion vector (BCMV) of a block could be derived when model parameters are confirmed. Then a set of candidate motion vectors (CMVs) could be obtained by modifying the BCMV. Thereafter, template matching is used to choose the optimal CMV (OCMV). Finally, the block is coded with the optimal CMV as an independent mode, and a rate distortion (RD) criterion is used to determine whether to use the mode or not. Experimental results demonstrate that by implementing the proposed method into Key Technology Area test platform version 2.6r1 (KTA2.6r1), a maximum -21.99% and average -8.72% bit rate savings can be achieved for videos involving zoom motion, while maintaining the same quality (evaluated by PSNR) of reconstructed videos when IPPPP coding structure is used. When Hierarchical B coding structure is employed, the maximum and average bit rate savings are -10.48% and -5.575% when the qualities of reconstructed videos remain unchanged. Besides, for videos involving camera rotation, translation, etc., an average -2.04% bit rate savings could also be achieved; while for videos containing common motions, an average -1.19% bit rate saving could be achieved at the same quality of reconstructed videos.