Abnormal Video Sections Detection Based on Inter-frames Information

An approach is proposed for abnormal sections detection in video sequences. In this approach, firstly the histogram is selected to describe the color change in the section, and then the histograms of the frames selected from the section compose the histogram matrix. In order to improve the process efficiency, the principal components analysis (PCA) is used to reduce dimensions of the histogram matrix. Secondly the information of frames differences is used to describe the motion change information, and the information twice frame difference is used to describe the change rate. Lastly, the results gotten from the features are fused to get the final result. This method is experimented with some samples. The results show that this method can realize the abnormal detections and rank classification of video sequences, and the results are better than the other related techniques.