ITM Web Conf.
Volume 32, 2020International Conference on Automation, Computing and Communication 2020 (ICACC-2020)
|Number of page(s)||5|
|Published online||29 July 2020|
CROWD ABNORMAL BEHAVIOUR DETECTION USING DEEP LEARNING
1 Department of Information Technology, Ramrao Adik Institute of Technology, Navi Mumbai, India
2 Department of Information Technology, Ramrao Adik Institute of Technology, Navi Mumbai, India
3 Department of Information Technology, Ramrao Adik Institute of Technology, Navi Mumbai, India
4 Department of Information Technology, Ramrao Adik Institute of Technology, Navi Mumbai, India
Crowd analysis has become an extremely famous research point in the territory of computer vision. Computerized examination of group exercises utilizing reconnaissance recordings is a significant issue for public security since it permits the identification of hazardous groups and where they’re going. We all see how many problems are faced because of the crowd. In our country, many terrorists are there. They plant a bomb in a crowded area which causes a lot of injuries. Thieves are mostly found or always leave in crowded areas so they can easily get an advantage of the crowd. In that situation, crowd analysis is very important. This paper presents the design of the deep learning architecture that provides control over the crowd behavior that will help to avoid violence or any other act which occurs because of the crowd which causes harmful effects to the society. So we are proposing a system that detects abnormal behavior of crowds using deep learning techniques.
Key words: Crowd analysis / pre-processing / object tracking / CCTV / Machine Learning / CNN / event behavior recognition
© The Authors, published by EDP Sciences, 2020
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