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A Multimodal Fusion Behaviors Estimation Method for Public Dangerous Monitoring.

Authors :
Hou, Renkai
Xu, Xiangyang
Dai, Yaping
Shao, Shuai
Hirota, Kaoru
Source :
Journal of Advanced Computational Intelligence & Intelligent Informatics; May2024, Vol. 28 Issue 3, p520-527, 8p
Publication Year :
2024

Abstract

At the present stage, the identification of dangerous behaviors in public places mostly relies on manual work, which is subjective and has low identification efficiency. This paper proposes an automatic identification method for dangerous behaviors in public places, which analyzes group behavior and speech emotion through deep learning network and then performs multimodal information fusion. Based on the fusion results, people can judge the emotional atmosphere of the crowd, make early warning, and alarm for possible dangerous behaviors. Experiments show that the algorithm adopted in this paper can accurately identify dangerous behaviors and has great application value. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13430130
Volume :
28
Issue :
3
Database :
Complementary Index
Journal :
Journal of Advanced Computational Intelligence & Intelligent Informatics
Publication Type :
Academic Journal
Accession number :
177325996
Full Text :
https://doi.org/10.20965/jaciii.2024.p0520