Abnormal Event Detection Based on Crowd Density Distribution and Social Force Model

摘要

In this study, we proposed a new method for the detection of abnormal event based on the social force model (SFM), combined with the local density information of the crowd. The method extracts the local density of the people based on the feature point clustering algorithm. The Latent Dirichlet Allocation (LDA) model is established based on the bag of words method combined with the temporal and spatial features of visual words, then identify the abnormal event using the maximum likelihood function.