[1] Mehran R, Oyama A, Shah M. Abnormal crowd behavior detection using social force model. [C]∥2009 IEEE Conference on Computer Vision and Pattern Recognition, June 20-25, 2009, Miami, FL, USA. New York: IEEE, 935-942(2009).
[4] Xiong G G, Cheng J, Wu X Y et al. An energy model approach to people counting for abnormal crowd behavior detection[J]. Neurocomputing, 83, 121-135(2012).
[5] Ravanbakhsh M, Nabi M, Mousavi H et al. Plug-and-play CNN for crowd motion analysis: an application in abnormal event detection. [C]∥2018 IEEE Winter Conference on Applications of Computer Vision (WACV), March 12-15, 2018, Lake Tahoe, NV, USA. New York: IEEE, 1689-1698(2018).
[6] Hu X, Huang Y P, Zhang H L et al. Video anomaly detection using deep incremental slow feature analysis network[J]. IET Computer Vision, 10, 258-267(2016).
[7] Zhang X S, Zhang H W, Zhang Y D et al. Deep fusion of multiple semantic cues for complex event recognition[J]. IEEE Transactions on Image Processing, 25, 1033-1046(2016).
[9] Farnebäck G. Two-frame motion estimation based on polynomial expansion[M]. ∥Bigun J, Gustavsson T. Image analysis. Lecture notes in computer science. Berlin, Heidelberg: Springer, 2749, 363-370(2003).
[10] Newman M E J, Girvan M. Finding and evaluating community structure in networks[J]. Physical Review E, 69, 026113(2004).
[11] Zeigarnik B, Ellis W D[M]. A sourcebook of gestalt psychology(1967).
[15] Rabiee H, Haddadnia J, Mousavi H et al. Novel dataset for fine-grained abnormal behavior understanding in crowd. [C]∥2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), August 23-26, 2016, Colorado Springs, CO, USA. New York: IEEE, 95-101(2016).