Abstract
With the advancement of technology, the detection of abnormal events in videos has extensive theoretical and practical significance. Most events in videos are normal events, but a small number of abnormal events contain a lot of information. How to identify individual abnormal events from massive videos is the focus of concern. The paper made full use of the spatio-temporal continuity of video images. Firstly, a space-time cube was constructed by integrating optical flow information; secondly, a multi-layer three-dimensional convolutional neural network model was constructed; finally, the entire process of video abnormal event detection was realized based on this model. The experiment on the UCSD dataset showed that the method in this paper can effectively detect abnormal events in videos.
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