A Classification Algorithm of Abnormal Crowd Behavior Based on Intensities

被引：0
|
作者：
Wang, XiaoFei [1 ]
Zhou, Xinyi [1 ]
Hu, Jun [1 ,2 ]
Kuang, Yin [1 ,3 ]
Tan, PanPan [1 ]
机构：
[1] Chengdu Normal Univ, Coll Comp Sci, Chengdu, Peoples R China
[2] Chengdu Normal Univ, Inst Intelligent Comp & Informat Technol, Chengdu, Peoples R China
[3] Chengdu Informat Technol Chinese Acad Sci Co Ltd, Postdoctoral Stn, Chengdu, Peoples R China
来源：
3RD INTERNATIONAL CONFERENCE ON MECHANICS, DYNAMIC SYSTEMS AND MATERIAL ENGINEERING (MDSME 2015) | 2015年
关键词：
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The occurrence of crowd abnormal behavior tends to pose harm to the social public security, while the crowd abnormal behavior at different levels would create different kinds of harm, accompanied by different focus and sensitivity. With this in mind, this paper has proposed a classification algorithm of crowd abnormal behavior based on intensities, which is verified in terms of its feasibility and accuracy with experiments.
引用
收藏
页码：138 / 141
页数：4
相关论文
共 50 条
  • [21] Research on the Detection Algorithm for Abnormal Crowd Behaviors Based on an Enhanced SlowFast Model
    Peng, Yueping
    Hao, Hexiang
    Zhou, Tongtong
    Han, Baixuan
    Yin, Wenji
    2024 9TH INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION SYSTEMS, ICCCS 2024, 2024, : 67 - 72
  • [22] Analyzing Tracklets for the Detection of Abnormal Crowd Behavior
    Mousavi, Hossein
    Mohammadi, Sadegh
    Perina, Alessandro
    Chellali, Ryad
    Murino, Vittorio
    2015 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV), 2015, : 148 - 155
  • [23] ABNORMAL CROWD BEHAVIOR DETECTION IN VIDEO SYSTEMS
    Tokta, Aybars
    Hocaoglu, A. Koksal
    2016 24TH SIGNAL PROCESSING AND COMMUNICATION APPLICATION CONFERENCE (SIU), 2016, : 697 - 700
  • [24] A review on classifying abnormal behavior in crowd scene
    Afiq, A. A.
    Zakariya, M. A.
    Saad, M. N.
    Nurfarzana, A. A.
    Khir, M. H. M.
    Fadzil, A. F.
    Jale, A.
    Gunawan, W.
    Izuddin, Z. A. A.
    Faizari, M.
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2019, 58 : 285 - 303
  • [25] Detection Algorithm of Crowd Abnormal Event Based on Girvan-Newman Splitting
    Li Wentao
    Fu Han
    Hao Zhen
    Ten Yan
    Yan Lin
    Zhao Peiran
    Zhang Xuewu
    LASER & OPTOELECTRONICS PROGRESS, 2020, 57 (06)
  • [26] Abnormal Crowd Behavior Detection and Location Based on Spatial-temporal Cube
    Hu X.
    Yu J.
    Deng C.
    Song S.
    Chen Q.
    Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2019, 44 (10): : 1530 - 1537
  • [27] A Crowd Behavior Model Based on Reciprocal Velocity Obstacle Algorithm
    Li, Xiaona
    Qin, Wenhu
    2012 INTERNATIONAL WORKSHOP ON INFORMATION AND ELECTRONICS ENGINEERING, 2012, 29 : 2887 - 2893
  • [28] Abnormal Crowd Behavior Detection Based on Combined Approach of Energy Model and Threshold
    Halbe, Madhura
    Vyas, Vibha
    Vaidya, Yogita M.
    PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PREMI 2017, 2017, 10597 : 187 - 195
  • [29] Abnormal Behavior Learning Based on Edge Computing toward a Crowd Monitoring System
    Miao, Yiming
    Yang, Jun
    Alzahrani, Bander
    Lv, Guoguang
    Alafif, Tarik
    Barnawi, Ahmed
    Chen, Min
    IEEE NETWORK, 2022, 36 (03): : 90 - 96
  • [30] Crowd Abnormal Behavior Recognition in Intelligent Surveillance System
    Zhao, Ying
    Zhou, Tianfei
    Wei, Shaoqian
    INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY, PTS 1-4, 2013, 263-266 : 2592 - +
12345