Histograms of Optical Flow Orientation for Visual Abnormal Events Detection

Abstract : In this paper, we propose an algorithm to detect abnormal events based on video streams. The algorithm is based on histograms of the orientation of optical flow descriptor and one-class SVM classifier. We introduce grids of Histograms of the Orientation of Optical Flow (HOFs) as the descriptors for motion information of the monolithic video frame. The one-class SVM, after a learning period characterizing normal behaviors, detects the abnormal events in the current frame. Extensive testing on benchmark dataset corroborates the effectiveness of the proposed detection method.