A New Network-Based Algorithm for Human Activity Recognition in Videos

被引：22

作者：

Lin, Weiyao ^{[1
]}

Chen, Yuanzhe ^{[1
]}

Wu, Jianxin ^{[2
]}

Wang, Hanli ^{[3
,4
]}

Sheng, Bin ^{[5
]}

Li, Hongxiang ^{[6
]}

机构：

[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200240, Peoples R China

[2] Nanjing Univ, Natl Key Lab Novel Software Technol, Nanjing 210023, Jiangsu, Peoples R China

[3] Tongji Univ, Dept Comp Sci & Technol, Shanghai 200092, Peoples R China

[4] Tongji Univ, Minist Educ, Key Lab Embedded Syst & Serv Comp, Shanghai 200092, Peoples R China

[5] Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, Shanghai 200240, Peoples R China

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

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY | 2014年 / 24卷 / 05期

基金：

美国国家科学基金会;

关键词：

Activity recognition; network model; video surveillance; TRACKING;

D O I：

10.1109/TCSVT.2013.2280849

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 new network-transmission-based (NTB) algorithm is proposed for human activity recognition in videos. The proposed NTB algorithm models the entire scene as an error-free network. In this network, each node corresponds to a patch of the scene and each edge represents the activity correlation between the corresponding patches. Based on this network, we further model people in the scene as packages, while human activities can be modeled as the process of package transmission in the network. By analyzing these specific package transmission processes, various activities can be effectively detected. The implementation of our NTB algorithm into abnormal activity detection and group activity recognition are described in detail in this paper. Experimental results demonstrate the effectiveness of our proposed algorithm.

引用

页码：826 / 841

页数：16

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