Real Life Violence Detection

16/06/20 REAL LIFE VIOLENCE DETECTION GitHub -  Source Code MENTOR: ANUGRAH SRIVASTAVA PROJECT MEMBERS: KOMATI NIKHILESWAR SHASHIDHAR POLOJU ADITYA SRIRAM SREYA CHEBIYYAM JOHN VARKEY INTRODUCTION: Automatic recognition of violence between individuals or crowds in videos has a broad interest. In this work, an end-to-end deep neural network model for the purpose of recognizing violence in videos is proposed. The proposed model uses a pre-trained MobileNet on ImageNet as a spatial feature extractor followed by a Time Distributed layer along with  Gated Recurrent Units (GRU) as a temporal feature extractor and also to extract meaningful actions from images and sequence of fully connected layers for classification purpose. The achieved accuracy is near state-of-the-art. Real-Life Violence Situations which contain 2000 short videos divided into 1000 violence videos and 1000 non-violence videos is used for fine-tuning the proposed models achieving the best accuracy of  97.0%. PROJECT DESCRIPT