Crowd emotion evaluation based on fuzzy inference of arousal and valence

NEUROCOMPUTING

卷:445

Article

Zhang, Xuguang¹  Yang, Xiuxin¹  Zhang, Weiguang¹  Li, Gongfa²  Yu, Hui³ 

[1] Hangzhou Dianzi Univ, Hangzhou 310018, Peoples R China

[2] Wuhan Univ Sci & Technol, Minist Educ, Key Lab Met Equipment & Control Technol, Wuhan, Peoples R China

[3] Univ Portsmouth, Portsmouth PO1 2DJ, Hants, England

关键词: Crowd behavior analysis;    Crowd emotion evaluation;    Fuzzy inference;    Emotional model;    Arousal and valence;    Crowd surveillance;   

DOI  :  10.1016/j.neucom.2021.02.047

来源: Elsevier

【 摘 要 】

Crowd behavior analysis is an important research topic in the field of video surveillance and public safety management. Crowd emotion has a strong relation with the crowd behavior. However, it is very challenging to predict crowd emotion using conventional emotion clues of humans from the video surveillance data, e.g. facial expression or body gesture. To tackle this challenge, this paper presents a crowd emotion evaluation method using fuzzy inference according to the arousal-valence model of the crowd movement. Specifically, the enthalpy, magnitude variance, confusion index and crowd density are extracted to describe crowd emotion. The enthalpy value and magnitude variance are taken as the input of the fuzzy inference system of arousal. And the confusion index and crowd density are used as the input of the fuzzy system of valence. The arousal value and valence value are the output respectively. Through establishing the relationship between arousal, valence and crowd features, the fuzzy rules are constructed to infer the emotion in the crowd scene. Experimental results show that the proposed method can effectively evaluate the arousal and valence in crowd emotion. (c) 2021 Elsevier B.V. All rights reserved.

【 授权许可】

Free