Abstract:

In order to effectively reduce the data dimension and remove the information of video data and improve the efficiency of abnormal event detection, the video abnormal event detection method based on the distinction and correlation is proposed. The method extracts features of the video data by analyzing the temporal and spatial neighborhood information of data, removes redundant information in the feature set and improves the efficiency of abnormal event detection by analysis of the distinction and correlation of feature. The method is compared with the traditional method in the simulation. The experimental results show that the detection accuracy of video abnormal event detection method based on feature fusion is higher than other methods, the method can accurately locate the abnormal area in the scene.

Key words: feature fusion, abnormal event, feature selection, correlation analysis