Weakly supervised anomaly detection method based on temporal consistency

Abstract

The invention discloses a weak supervision abnormal behavior detection method based on time sequence consistency. The method comprises the following steps: constructing a behavior detection system, importing a behavior video pair into the behavior detection system, and forming a time sequence matrix constructed by the behavior video pair after processing. Based on the temporal consistency and smoothing characteristic of human behavior, a behavior unit pair is formed to obtain relevant behavior segments, and the start and end frames of relevant abnormal actions in the behavior segments are located. Based on weak supervision, the obtained behavior segments are learned to obtain the operation classifier which can judge various behavior characteristics. Based on dictionary learning and solvingthe detection criteria of judging behavior features in sparse coding reconstruction operation classifier, a new behavior judgment logic is formed to detect various abnormal behavior classes. The weakly supervised abnormal behavior detection method provided by the invention is easy to learn the characteristics of the related behavior classification without manually labeling the boundary of the frame to establish the related behavior model.

Description

technical field [0001] The invention relates to the technical field of image processing, and relates to a method for detecting abnormal behaviors, in particular to a method for detecting abnormal behaviors with weak supervision based on timing consistency. Background technique [0002] The abnormal behavior detection method based on weak supervision is a research hotspot of scholars at home and abroad. Its main principle is to use the temporal consistency and smoothness of human behavior to form a behavior unit pair, and locate the start and end frames of related abnormal actions in the video. , and train the corresponding action classifier, and then perform abnormal behavior detection based on sparse reconstruction. The key to the weakly supervised abnormal behavior detection method is how to locate the start and end frames of the relevant abnormal action classes in the video. [0003] Most of the existing abnormal behavior detection uses artificial features. However, arti...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to solve the problem of high computational complexity of artificial features in the prior art, and it is difficult to select and design an effective behavior feature in complex scenarios, and to provide a weakly supervised abnormal behavior detection method based on timing consistency , the specific technical scheme is as follows:

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