Violence Detection Using Computer Vision Approaches

Violent crime has always been a major social problem. The rise of violent behavior in public areas can be attributed to a variety of factors. Greed, frustration, and hostility among individuals, as well as social and economic anxieties, are the primary causes of increased violence. It is critical to protect our possessions, as well as our lives, from threats such as robbery or homicide. It is impossible to prevent crime and violent acts unless brain signals are studied and a certain pattern deduced from criminal ideas is detected in real-time. Due to its technological viability, it has yet to be realized. However, We can identify violent activity in public spaces by using the concepts of computer vision (a subfield of deep learning) technology. The goal of this project is to build a real-time violent activity monitoring system that will be capable of detecting violence very quickly and efficiently. The public of any city can benefit from it, as it will allow the people of the law enforcement department to take necessary actions to prevent violent activities. When the system is implemented, it will be able to detect the speed of the movements of people and their distances from other people walking in public places by using cameras. The system will mainly detect the speed of hand and leg movements of a person who will be very close to another person. If anyone is identified as a violent maker, the server-side of the system will notify the people who will be responsible for preventing violence in a very short time. The system was built using the concepts of computer vision and neural networks. The system has been developed and tested initially on the personal computing devices of the system developers. This system is very easy to design and develop, making it very easy to use for any kind of public area surveillance. At the same time, the system gives its desired output due to its high accuracy.