Model Based Motion Vector Predictor for Zoom Motion

摘要

As zoom motion is common in video applications, a linear motion model is derived to describe zoom motion based on the analyses of camera imaging principles. Based on the motion model, a motion vector predictor for videos involving zoom motion is proposed. A rate distortion (RD) criterion is used to choose the optimal motion vector predictor between the one utilized in H.264/AVC and the one derived from the linear motion model. Experimental results demonstrate that by implementing the proposed method into Key Technology Area test platform version 2.2r1(KTA2.2r1), the maximum and average bit rate savings can be achieved as high as 7.66% and 4.90% respectively, while maintaining the same quality of reconstructed videos.