Macroblock Classification Method for Video Applications Involving Motions

被引：31

作者：

Lin, Weiyao ^{[1
]}

Sun, Ming-Ting ^{[2
]}

Li, Hongxiang ^{[3
]}

Chen, Zhenzhong ^{[4
]}

Li, Wei ^{[5
]}

Zhou, Bing ^{[6
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Image Commun & Informat Proc, Dept Elect Engn, Shanghai 200240, Peoples R China

[2] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA

[3] Univ Louisville, Dept Elect & Comp Engn, Louisville, KY 40292 USA

[4] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore

[5] Beihang Univ, Sch Comp Sci & Engn, Beijing 100083, Peoples R China

[6] Zhengzhou Univ, Sch Informat Engn, Zhengzhou 450001, Peoples R China

来源：

IEEE TRANSACTIONS ON BROADCASTING | 2012年 / 58卷 / 01期

基金：

美国国家科学基金会;

关键词：

MB classification; motion information; SCENE-CHANGE DETECTION; RECOGNITION;

D O I：

10.1109/TBC.2011.2170611

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a macroblock classification method is proposed for various video processing applications involving motions. Based on the analysis of the Motion Vector field in the compressed video, we propose to classify Macroblocks of each video frame into different classes and use this class information to describe the frame content. We demonstrate that this low-computation-complexity method can efficiently catch the characteristics of the frame. Based on the proposed macroblock classification, we further propose algorithms for different video processing applications, including shot change detection, motion discontinuity detection, and outlier rejection for global motion estimation. Experimental results demonstrate that the methods based on the proposed approach can work effectively on these applications.

引用

页码：34 / 46

页数：13

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