Anomaly Detection in Crowd Scenes using Streak Flow Analysis

A new approach is proposed to analysis and localize abnormal events in crowded scenes, such us detecting suspicious behavior, sudden assemble and dispersion of pedestrian in the crowd scenes. The proposed methodology uses streak flow technique along with LDA (Latent Dirichlet Allocation)to detect anomalies in crowd scenes. This method divides the frames into blocks for accurate representation of spatial and temporal changes in scene. Optical flow algorithm is used to estimate the motion and direction of the pedestrian in crowd scene. Crowd flow motion is extracted using streak flow with the combination of streak line and potential functions. Experimental result shows that the detection of abnormalities in crowd scenes using streak flow approach gives better accuracy of 93.37% than the state of Art of techniques.