Title: Simple multi-scale human abnormal behaviour detection based on video
Authors: Gang Ke; Ruey-Shun Chen; Yeh-Cheng Chen; Yu-Xi Hu; Tsu-Yang Wu
Addresses: Department of Computer Engineering, Dongguan Polytechnic, Dongguan, Guangdong, China ' Department of Computer Engineering, Dongguan Polytechnic, Dongguan, Guangdong, China ' Department of Computer Science, University of California, Davis, CA, USA ' School of Software, Northwestern Polytechnical University, Xian, Shanxi, China ' College of Information Science and Technology, Shandong University of Science and Technology, Qindao, Shandong, China
Abstract: Aiming at the problem of real-time and low accuracy of automatic recognition of human abnormal behaviour in a public area surveillance video, a simple multi-scale human anomaly behaviour detection algorithm based on video was proposed. Firstly, the binary image sequence of human body in surveillance video is acquired by background modelling method based on visual background extraction (ViBe). Then, the simple multi-scale algorithm is constructed by combining the aspect ratio, motion trajectory and video continuous interframe motion acceleration of the minimum circumscribed rectangle of the binarised image. The human target behaviour is judged, and then the normal behaviour of the human body - standing, walking, jogging, and abnormal behaviour - shouting for help, falling, punching, wandering, and sudden running are identified. The experimental results show that the human body moving target recognition by ViBe combined with simple multi-scale algorithm for abnormal behaviour detection has good real-time performance and high accuracy.
Keywords: pedestrian recognition; anomalous behaviour detection; ViBe algorithm; simple multi-scale algorithm; surveillance video.
DOI: 10.1504/IJICS.2022.122376
International Journal of Information and Computer Security, 2022 Vol.17 No.3/4, pp.310 - 320
Received: 20 Mar 2019
Accepted: 18 Apr 2019
Published online: 22 Apr 2022 *