Method for detecting group crowd abnormal behaviors in video monitoring

A technology of video surveillance and detection method, which is applied in the field of video surveillance application and technology integration, and can solve problems such as occlusion or local gathering, environment interference crowd target recognition system, etc.

Inactive Publication Date: 2012-11-28
安吉安融智能科技有限公司
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems existing in the prior art, such as the dynamic movement of crowds, occlusion or local gathering problems, and environmental interference affecting the crowd target recognition system among sports crowds, the present invention provides a group based on video surveillance The method for detecting crowd abnormal behavior includes the following steps:

Method used

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  • Method for detecting group crowd abnormal behaviors in video monitoring

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Embodiment Construction

[0051] The method of the present invention will be further described below in conjunction with the drawings.

[0052] Such as figure 1 As shown, the method for detecting group crowd abnormal behavior in video surveillance of the present invention can be divided into four steps: crowd detection, crowd target tracking, group crowd classification, and crowd abnormal behavior recognition, each of which can be divided into multiple small steps.

[0053] Canny edge finding

[0054] The process of Canny edge finding is to first smooth the image by Gaussian convolution, then use the non-maximum gradient value to suppress and refine the edge, and finally use the hysteresis threshold to add the weak edge connected to the strong edge to the edge image.

[0055] Motion edge

[0056] The process of obtaining the moving edge is to make the difference between the edge images of two consecutive frames of video images to eliminate the influence of the static scene.

[0057] Background frame maintenance...

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Abstract

The invention provides a method for detecting group crowd abnormal behaviors in video monitoring. The method comprises the steps of: video target detection: obtaining video objects through edge information difference detection in successive frames, and obtaining video objects with movement change through frame difference of a foreground frame and a background frame, obtaining a relatively accurate movement target by combining two video object detection results; video target tracking: tracking targets to obtain corresponding movement tracks through a video particle-based long-period movement estimation method; group crowd detection: carrying out spectral clustering analysis on the distance between the tracks and advancing speed information through movement characteristics of the group crowd in video; and identification of group crowd abnormal behaviors: establishing a model for crowd tracks by using an MGHMM (Mixed Gaussian Hidden Markov Model), and identifying blockage and fall through sudden change of a normal track. The invention integrates technologies of crowd target detection, group target track, mode identification and machine learning.

Description

Technical field [0001] The invention relates to a method for detecting abnormal behavior of crowds, in particular to a method for detecting abnormal behaviors of group crowds based on video monitoring analysis, and belongs to the field of video monitoring applications and technology integration. Background technique [0002] Although the current intelligent surveillance system for crowd recognition has received some attention in recent years, most studies have focused on determining the number of people in a small spatial area (which has been calculated in the crowd calculation and tracking paradigm). There are relatively few researches on crowd behavior analysis, and there are few related researches that can solve population detection and tracking at the level of medium-density or small group. [0003] The intelligent monitoring system for the crowd consists of four main parts: crowd detection, crowd tracking, crowd classification and crowd abnormal behavior recogniti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
Inventor 章东平陈非予彭怀亮
Owner 安吉安融智能科技有限公司
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