Title:

OS16-1 A Method of Detecting Abnormal Crowd Behavior Events Applied in Air Patrol Robot

Publication: ICAROB2017
Volume: 22
Pages: 181-185
ISSN: 2188-7829
DOI: 10.5954/ICAROB.2017.OS16-1
Author(s): Huailin Zhao, Shunzhou Wang, Shifang Xu, Yani Zhang, Masanori Sugisaka
Publication Date: January 19, 2017
Keywords: Air Patrol robot, Abnormal event detection, Gaussian process regression
Abstract: When the ground or air patrol robot monitors a certain area, one of the important intelligent functions is to estimate the crowd density of the monitored area. This paper analyzes the crowd density estimation algorithm, and use a Gaussian process regression model for crowd density estimation. Through the crowd density estimation and changes, we can detect abnormal behavior events of the crowd. The method can not only estimate the population density of the specified area, but also analyze and detect the abnormal behavior events of the crowd. This application provides an important technical support for enhancing the patrol robot monitoring effect.
PDF File: https://alife-robotics.co.jp/members2017/icarob/data/html/data/OS_pdf/OS16/OS16-1.pdf
Copyright: © The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
See for details: https://creativecommons.org/licenses/by-nc/4.0/

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