Abnormal Activity Detection based on MCRF
Zhao Long, Bo Gao, Zheng Guoqiang, Wang Xin, Rujia Qiu, Xiao Wenjun · 2018
Abnormal activity detection based on MCRF (Multiple Conditional Random Fields) model is proposed. The advantage of MCRF model is the ability of combining more Features of abnormal activity and utilizing adaptive contextual information. Several features subsets can be formed through more features extraction. Then we made use of CRF (Conditional Random Fields) model to each feature subset and got CRF units. Finally, we combined all the CRF units to produce MCRF model which was utilized to detect abnormal activity. The experimental results indicate that the detection accuracy rate of this method is better. And the time of Model training is reduced by Parallel Processing.