Real Time Analysis of Crowd Behaviour for Automatic and Accurate Surveillance
E. Padmalatha, Karedla Anantha, Dasarada Ram · International Journal of Advanced Computer Science and Applications · 2019
Surveillance in this modern era is a necessity. Creating an alert in case of emergencies and disturbances is of very much importance. As the number of simultaneous camera feeds increase, burden on human supervisor also increases. The proposed system is a way to aid human supervisor in the surveillance job. Creating alerts in real time will help responding quickly to crucial situations. With this in mind, we propose the following things: (1) Generation of ViF (Violent Flow Descriptors) as high-level features in real time. (2) Using generated ViF’s of a Video Dataset for training a neural net and testing its accuracy.(3) Developing a system that can detect the signs of disturbance among the crowd in real time and can learn from the decisions it makes.