Optical Technique, Volume. 47, Issue 2, 187(2021)

Abnormal crowd behavior detection using improved C3D-RF under Video Surveillance

ZHANG Weiwei1、*, CHEN Suiyang2, and CHEN Rui3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    References(9)

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    [5] [5] Xuan Q, Li F, Liu Y, et al. MV-C3D: A spatial correlated multi-view 3D convolutional neural networks[J]. IEEE Access,2019,7(01):2169—3536.

    [8] [8] Qian H M, Mao Y B, Wang Z Q. SVM-based abnormal activity detection for home care[C]∥2008 7th World Congress on Intelligent Control and Automation.China,Chongqing:IEEE,2008:3766—3771.

    [11] [11] Guo S, Bai Q, Gao S, et al. An analysis method of crowd abnormal behavior for video service robot[J]. IEEE Access,2010,07(01):169577—169585.

    [15] [15] Direkoglu C. Abnormal crowd behavior detection using motion information images and convolutional neural networks[J]. IEEE Access,2020,08(01):80408—80416.

    [18] [18] Hu X, Dai J, Huang Y P, et al. A weakly supervised framework for abnormal behavior detection and localization in crowded scenes[J]. Neurocomputing,2020,383(01):270—281.

    [23] [23] Pinter M. Toward more realistic pathfinding[EB/OL]. (2001-03)/[2001-09].http:∥www.gamasutra.com/view/feature/3096/toward_more_realistic_pathfinding.php.

    [24] [24] Ferryman J, Ellis A L. Performance evaluation of crowd image analysis using the PETS2009 dataset[J]. Pattern Recognition Letters,2014,44(15):3—15.

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    ZHANG Weiwei, CHEN Suiyang, CHEN Rui. Abnormal crowd behavior detection using improved C3D-RF under Video Surveillance[J]. Optical Technique, 2021, 47(2): 187

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    Paper Information

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    Received: Aug. 31, 2020

    Accepted: --

    Published Online: Sep. 9, 2021

    The Author Email: Weiwei ZHANG (15129936628@163.com)

    DOI:

    CSTR:32186.14.

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