Programs
- M. Tech. in Automotive Engineering -
- B. Sc. Clinical Nutrition, Dietetics, and Food Science - Undergraduate
Publication Type : Journal Article
Publisher : Science Direct
Source : The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems, pp.157-171. (SCOPUS)
Url : https://www.sciencedirect.com/science/article/abs/pii/B9780128163856000118
Campus : Chennai
School : School of Engineering
Department : Computer Science and Engineering
Year : 2020
Abstract : There is an increasing demand for automated video surveillance with a wide range of threats in the society and less manpower to monitor them. Especially, detecting violence in crowded scenes is challenging because of the rapid movement, overlapping features due to occlusion, and cluttered backgrounds. In this paper, we review the recent trends in violence detection and perform a comparative study of different state-of-the-art shallow and deep models using the Histogram of Oriented Optical Flow feature descriptor on the Crowd Violence and Hockey Fight data sets.
Cite this Research Publication : Roshan, S., Srivathsan, G., Deepak, K. and Chandrakala, S., 2020. Violence detection in automated video surveillance: Recent trends and comparative studies. The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems, pp.157-171. (SCOPUS)