Violence Detection for Smart Cities using Computer Vision

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There is a need for developing deep learning solutions to analyze videos to identify any violence being present. This paper proposes a method for the detection of the presence of violent activities in videos using Deep Neural Networks. Recently there has been a rapid development happening in the field of Deep Neural networks, but the number of solutions that have been developed for violence detection is very few. The proposed solution will play a major role in transforming the way law enforcement works and support the government’s initiative to make cities smarter. The model is built using CNN for video frame feature extraction and LSTM to capture localized features present in the video frames. The LSTM extracts the localized features using the spatiotemporal relationship between the video frames. The local motion present in the video is analyzed. This work focuses on accuracy and fast response time. The performance was evaluated on the hockey fight dataset to detect violent activities.