TO IDENTIFY SUSPICIOUS ACTIVITY FROM SURVEILLANCE FOOTAGE
International Journal of Progressive Research in Engineering Management and Science · 2024
High-quality CCTV cameras have been installed using a variety of technologies to ensure the protection of people and property.It is not feasible to manually keep an eye on every activity at all times.In this work, the concept of CNN is utilized to identify if behavior in an environment is suspicious or normal, and a system that alerts the similarity authority in the event that it predicts suspicious activity is proposed.It's important to remember that the deployment environment, the machine learning model's architecture, and the caliber of the training data all affect how successful a suspicious activity detection system.This paper focuses on a deep learning approach to detect suspicious human activity and fight using CNN from images and videos.We analyze different CNN architectures and compare their accuracy.We design our systems that can process video footage from cameras in real time and predict whether activity is suspicious or fight found or not.