Violent/Non-Violent Video Classification based on Deep Neural Network
Ninth International Conference on Advances in Pattern Recognition, ICAPR 2017
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.
Mondal, Sounak; Pal, Soumyajit; Saha, Sanjoy Kumar; and Chanda, Bhabatosh, "Violent/Non-Violent Video Classification based on Deep Neural Network" (2018). Conference Articles. 10.