Abstract： An anomaly detection algorithm based on the statistic feature of optical flow block was proposed. First, the whole optical flow field of training video sequences were obtained. Then, each optical flow field was divided into blocks and each block was preprocessed in order to extract the statistic feature considering both magnitude and phase information of the block. The Gaussian mixture model (GMM) was employed  to establish the probability model of normal behaviors by feeding the statistic feature into it. The abnormal degree of the optical flow block was judged by the output posterior probability of the GMM probabilistic model. The experimental results show that the method proposed considers both the consistency information of moving objects and the partial occlusion issue, at the same time, improves the accuracy of anomaly detection.