Violence Detection using Deep Learning Techniques

In the past years, human action recognition has been improved. Violence recognition is one of the best challenging research topics in the field of computer vision. Its one of the specific application is to find violence from surveillance cameras in public places, private places etc. We want an immediate control on these violent incidents. Human operator needed for monitoring the screen of surveillance video, which often leads to mistake and neglect to pinpoint the occurrence of unusual events, its require to them in a powerful search for automated violence detection systems. This paper discusses this research problem and explores LSTM and BiLSTM based solution to solve it. In addition, a layer of attention is present and used a new content database that collected from surveillance camera and normal recorded videos available on YouTube, Facebook etc. This database is publicly available. From the comprehensive tests conducted on Hockey Fight and dataset containing crowd and normal public scenes. It seems that BiLSTM model has more accuracy in the combat situation than LSTM model.