Optical flow and spatio-temporal gradient based abnormal behavior detection
Dongliang Jin, Songhao Zhu, Xian Sun, Zhiwei Liang, Guozheng Xu · 2016
To improve the accuracy of the detection of local abnormal behavior, a novel method is here proposed. The main idea of the proposed method is described as follows: firstly, a video sequence is divided into spatio-temporal blobs; then, a statistical method based on the semi-parametric model is adopted to detect these blobs where abnormal behaviors most likely to appear; finally, maximum optical flow energy and local nearest descriptor are utilized to determinate whether these suspicious blobs really contain abnormal behaviors. The experimental results conducted on UCSD dataset demonstrate the effectiveness of the proposed method.