Anomaly Detection in Crowd Scene Using Interaction Force Model
Chonthisa Wateosot · Asia-Pacific Journal of Science and Technology · 2017
Abnormal detection in crowded scene is an important issue in computer vision. Many researches have studied and tried to define the phenomena of crowd behavior. In this paper we introduce a novel social-based method for detecting abnormal events in crowded scenes, called Interaction Energy Force. The method is designed for low level features without object extraction and tracking. The force modeling based on optical flow fields and its interactions are defined by an energy force inspiring the energy propagation phenomena that depend on directions and velocities. An energy map is designed to represent the interaction forces corresponding to events, where the abnormal events are detected using a thresholding method. Our method is evaluated with the well-known UMN dataset. The results show the efficiency of our approach with high accuracy, regardless of various conditions. It is a technique competitive with the state-of-the-art methods.