Detection Algorithm of Crowd Abnormal Event Based on Girvan-Newman Splitting

被引:1
|
作者
Li Wentao [1 ]
Fu Han [1 ]
Hao Zhen [1 ]
Ten Yan [1 ]
Yan Lin [1 ]
Zhao Peiran [1 ]
Zhang Xuewu [1 ]
机构
[1] Hohai Univ, Coll Internet Things Engn, Changzhou 213022, Jiangsu, Peoples R China
关键词
machine vision; motion characteristics; GN splitting; abnormal event detection algorithm;
D O I
10.3788/LOP57.061506
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 terms of the problem that the traditional detection method of crowd abnormal events based on group motion state analysis does not describe the semantic information of scene adequately, the Girvan-Newman (GN) splitting up algorithm found by the community in the complex network is introduced. The pedestrians with similar motion characteristics and similar positions arc divided into multiple groups, and the differences among the groups in normal and abnormal scenes arc described and the occurrence of abnormal events is detected with the changes in group motion intensity and group number. Through experimental verification, the proposed algorithm can accurately detect abnormal events while enriching the semantic information of the scene.
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收藏
页数:7
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