Abnormal state detection method of medium and high density crowd

Abstract

The invention discloses an abnormal state detection method of a medium and high density crowd. The abnormal state detection method comprises the following steps: firstly, extracting and tracking feature points, and calculating the speed of each feature point according to the coordinates of the feature point in a previous frame of surveillance video image and a current frame of surveillance video image; then, adopting diagram analysis to obtain behavior consistency among the feature points, ejecting discrete points on the basis of the behavior consistency, and clustering the residual feature points; calculating the crowd aggregation degree, the crowd movement strength and the crowd movement direction variance of all feature points in a cluster; and according to the three parameters in multiple frames of surveillance video images and the amount and the amplification of the crowd cluster, judging the abnormal state of the crowd. The abnormal state detection method carries out crowd state analysis on the basis of a diagram analysis method to realize the detection of three crowd states including a crowd evacuation state, a crowd cluster state and a crowd disturbance state.

Description

technical field [0001] The invention belongs to the field of crowd gathering state detection, and more specifically, relates to a method for detecting abnormal state of medium and high-density crowds. Background technique [0002] With the improvement of people's living standards and the development of spiritual and cultural needs, large-scale and highly dense crowds can be seen everywhere: shopping malls, temples, railway stations and various celebrations. These public places have limited space, but there are often crowds of people and bustling scenes, behind which there are huge hidden safety hazards. Among them, the frequency of serious crowd abnormalities such as parades, gang fights, and stampedes is increasing rapidly. People's lives and properties have been seriously damaged. Therefore, in the face of the severe situation, how to effectively prevent the occurrence of crowd abnormalities and control the development of accidents is a major scientific and social issue. ...

AI Technical Summary

Problems solved by technology

A large number of people interact with each other in medium-to-high-density scenes, resulting in higher frequency of conflicts and collisions, blurred moving targets, mutual occlusion, and more complex behaviors of different people, all of which make the detection of the state of medium-to-high-density crowds more complicated.

[0004] At present, the traditional crowd abnormal state detection algorithm mainly has the following deficiencies: 1) The detected crowd objects are very limited

2) The parameters of the algorithm itself are complex, and whether the parameters are properly selected will directly affect the detection results of the algorithm

3) Algorithms are often limited by factors such as occlusion, crowding, and low resolution between pedestrians, and ignore the interaction between pedestrians

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