Content area

Abstract

The abnormal event detection becomes an important topic recently. This paper presents a method to detect the crowd gathering, as well as the commotion event after the crowd gathering. The proposed stillness model and the motion model are based on the improved background subtraction and the optical flow feature. We construct the long-term stillness level by the break bucket model and clustering the instantaneous stillness level. Then the crowd gathering event is decided by the threshold with the long-term stillness level. Furthermore, the motion model is applied for detecting the commotion event after the crowd gathering. In the experiment, we used the dataset of PET2009. The proposed method is verified by the experiment with 97% accuracy.

Details

Title
Crowd gathering and commotion detection based on the stillness and motion model
Author
Deng-Shun, Yang 1 ; Chun-Yu, Liu 1 ; Wei-Hao, Liao 1 ; Shanq-Jang, Ruan 1 

 National Taiwan University of Science and Technology (NTUST), Department of Electronic and Computer Engineering, Taipei City, Taiwan (R.O.C.) 
Pages
19435-19449
Publication year
2020
Publication date
Jul 2020
Publisher
Springer Nature B.V.
ISSN
13807501
e-ISSN
15737721
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2432263392
Copyright
© Springer Science+Business Media, LLC, part of Springer Nature 2020.