.png){kind=icon}
.png){kind=icon}
Return
Model Based Motion Vector Predictor for Zoom Motion
.png){kind=icon}
PRE
AI
DOI：10.1109/LSP.2010.2055051.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
H.264/AVC
motion vector predictor
video coding
zoom motion
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.6
Papers:
1.1W
Citations:
1.7W