Women abuse Detection in Video Surveillance using Deep Learning

In this paper, we proposed women abuse detection method in surveillance video system. The proposed method consists of gender detection using convolutional neural networks (CNNs) for identifying both male and female are present in the location .The abuse action is then detected by using the 4 steps: i) Detection of object region by background subtraction method then apply the morphology filter to reduce noise artifacts. ii) Estimation of the motion vector using the Combined Local-Global approach with Total Variation (CLG-TV) iii) Detection of the abuse action by examining the characteristic of motion vectors produced by using the Motion Co-occurrence Feature (MCF).