A new method for violence detection based on the three dimensional scene flow
Wu Wang, Yunfei Cheng, Yuexia Liu · 2018
Violence detection from surveillance video is a challenging and attractive task. This paper introduce a new violence detection using binocular stereo vision. We use the sparse stereo matching method to extract the feature points of both rectified images and obtain the vision disparity of the point. The 3D coordinates of the points are calculated through the standard 3D measurement theory. To describe the spatio-temporal property, we extract features aligned with the trajectories to characterize depth information (Three-dimensional motion vector), appearance (histograms of oriented gradients) and motion (histograms of optical flow). In order to obtain the discriminative feature, this paper adopts sparse coding scheme and support vector machine (SVM) to classify the feature vector as normal or abnormal.