Violent/Non-Violent Video Classification based on Deep Neural Network

In the context of video surveillance, detecting violence is an important task. This work presents a deep neural network based novel video classification to label violence/non-violence classes. First of all, frame-level descriptors are constructed based on optical flow and variants of Weber Local Descriptor. A novel scheme is presented to summarize the frame-level descriptors in to the video-level descriptor. An architecture for deep neural network with four hidden layers is proposed to classify a video as violent or non-violent. Proposed method is tested on two benchmark datasets. Comparison of performance with state-of-the-art systems establishes the superiority of the proposed method.