Crowd fleeing event detection method and system based on direction-clustering model

A technology of event detection and clustering, which is applied to computer components, character and pattern recognition, instruments, etc., can solve the problems of being unable to apply to various densities of people and low accuracy

Active Publication Date: 2017-06-13
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] To sum up, the existing detection methods for crowd escape events have low detection accuracy and cannot be applied to escape events of various density crowds.

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  • Crowd fleeing event detection method and system based on direction-clustering model
  • Crowd fleeing event detection method and system based on direction-clustering model
  • Crowd fleeing event detection method and system based on direction-clustering model

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Embodiment Construction

[0071] It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0072] It should be noted that the terminology used here is only for describing specific embodiments, and is not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprise" and / or "comprise" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0073] The present invention defines "group behavior" as behavior in which more than 50 targets have coherent and uniform movement in a cert...

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Abstract

The invention discloses a crowd fleeing event detection method and system based on a direction-clustering model. In order to solve the problem that the crowd fleeing event detection method is low in detection accuracy, the technical scheme comprises the steps of extracting moving tracks from crowd monitoring videos, thereby obtaining a track coordinate matrix, and calculating speeds and directions of moving particles on the moving tracks through the track coordinate matrix; on the basis of the randomness of the speeds and directions of the moving particles, establishing the direction-clustering model which represents a moving state of a crowd; calculating a direction-clustering index of each frame of crowd monitoring video according to the direction-clustering model; extracting an event detection threshold self-adaptively from all obtained direction-cluster indexes, comparing the event detection threshold with the direction-clustering index of each frame of crowd monitoring video, and finally detecting a crowd fleeing event of the crowd monitoring video. The method is widely applied to a middle and high density crowd and the detection accuracy is high.

Description

technical field [0001] The invention belongs to the field of video detection, in particular to a method and system for detecting crowd escape events based on a direction-cluster model. Background technique [0002] In recent years, in order to prevent abnormal events such as crowd fights, crowding and stampedes, and crowds fleeing, more and more video surveillance equipment is spread in public areas such as streets, subway stations, and airports, followed by a dramatic increase in video transmission volume. increase. The traditional video surveillance system needs to detect anomalies artificially. This method is not only inefficient and the labor cost is too high, but also the monitoring personnel will experience visual fatigue after working for a long time, which will lead to a decrease in concentration, resulting in a high rate of false positives and false negatives. Increase. Therefore, as one of the main tasks of intelligent video monitoring points, using computers ins...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V20/42G06V20/53
Inventor 常发亮王梦迪张友梅
Owner SHANDONG UNIV
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