Model Based Motion Vector Predictor for Zoom Motion

• Published in: IEEE signal processing letters Vol. 17; no. 9; pp. 787 - 790
• Main Authors: Yuan, Hui, Chang, Yilin, Lu, Zhaoyang, Ma, Yanzhuo
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2010; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Automatic voltage control; Bit rate; Cameras; Criteria; Distortion; H.264/AVC; Image analysis; Image reconstruction; Mathematical analysis; Mathematical models; Motion analysis; motion vector predictor; Optimization; Platforms; Predictive models; Rate-distortion; Testing; Vectors; Vectors (mathematics); video coding; zoom motion
• DOI: 10.1109/LSP.2010.2055051
• ISSN: 1070-9908

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.