Abnormal behavior identification method based on contour

Abstract

The invention discloses a method for recognizing aberrant behaviors based on contours. The method is characterized in that the detection and the tracking of moving targets are primarily performed for the image sequences collected by a camera so as to extract target contours; then spatial information of the moving targets in each frame is indicated by utilizing R transformation; then the spatial information is rearranged and combined as characteristic vectors of behavior analysis and the characteristic dimension reduction is performed by adopting principal component analysis; finally the transformation relation of the contour sequences with spatial information in the time is indicated by utilizing a hidden Markov model, and all the behaviors can be indicated with respective parameters of the hidden Markov model. In the recognition process, the characteristic sequences of new behaviors are compared with the storage parameters, and the behaviors best matched are selected upon the maximum likelihood principle. Therefore, the method for recognizing aberrant behaviors has an important significance of automatic analysis for intelligent visual monitoring, so that time, places and characters of occurrence events in the scene can be known without assistance of the people; moreover, the method for recognizing aberrant behaviors also can be used for video retrieval so as to assist the people to seek for the interesting events in the video frequency.

Description

technical field [0001] The invention belongs to the field of pattern recognition, relates to technologies such as image processing and computer vision, and particularly relates to an abnormal behavior recognition method in intelligent visual monitoring. Background technique [0002] With the rapid development of modern technology, the use of cameras to monitor dynamic scenes has been widely used in all aspects of society. Except for some occasions with high security requirements, such as banks and military bases, more and more intelligent visual surveillance applications are used in civilian , such as traffic intersections, living communities, along subway lines, etc., to protect people's lives and property. Although the current commercial monitoring cameras generally exist in shopping malls, supermarkets, and elevator rooms, they do not give full play to their real-time and active monitoring and alarm functions. Although these cameras can provide a large amount of video da...

AI Technical Summary

Problems solved by technology

[0005] Traditional monitoring can realize the distribution and storage of video data, but the abnormal situation in the scene can only be handled manually

In the face of massive video data, continuous long-term work will make the guards tired, not vigilant, and insensitive to dangerous events

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