Study on the Method of Detecting the Crowd Abnormality in the Sensitive Media Image Based on Behavior Analysis

During the process of detecting crowd abnormality in sensitive multimedia image region, prone to severe occlusion. The detection process of traditional sensitive multimedia image region crowd abnormality based on cell movement characteristic, due to occlusion interference, the extracted motion feature is not accurate, thus, it is unable to obtain accurate crowd abnormality detection results, a sensitive multimedia image region crowd abnormality detection method based on behavior analysis is proposed, Hu invariant moment features as crowd abnormality feature is input into RBF neural network, through learning and classifying the RBF neural network, to access crowd abnormality of various types. Calculating and analyzing NMI of sensitive multimedia video image at each time moment, based on the analysis result of the crowd abnormality set a reasonable threshold, and complete the detection the crowd abnormality in sensitive multimedia image regions. The simulation results show that the proposed method has high detection accuracy.