An Abnormal Event Recognition in Crowd Scene

Real-world actions occur often in crowded, dynamic environments. This poses a difficult challenge for current approaches to video event detection because crowd scenes are always extremely cluttered. In this paper, we design a video content analysis method for fighting event recognition in crowd scene. Our method begins with four MPEG-7 descriptors: crowd kinetic energy, motion directions histogram, spatial distribution parameter and spatial localization parameter of two adjacent frames. Then the support vector machines (SVMs) method is introduced to train and test these descriptors for fighting event recognition. Extensive experimental results have demonstrated that our method is effective in fighting events recognition with low error rates and can be easily adopted in fixed camera environment with real time application.