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Group abnormal behavior identification method

A recognition method and behavior technology, applied in the field of data recognition, can solve problems such as large calculation load and affect the real-time detection, and achieve the effect of high accuracy and meet the real-time requirements of the system.

Active Publication Date: 2020-02-11
杭州视鑫科技有限公司
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AI Technical Summary

Problems solved by technology

Abnormal behavior of multiple people refers to fighting behavior and panic behavior of multiple people in non-single-person scenes. If the characteristics of each person in the monitoring scene are extracted for behavior analysis, a huge amount of calculation will be generated, which will directly affect the real-time performance of detection.

Method used

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Embodiment Construction

[0026] The present invention will be described in further detail below in conjunction with the examples, but the protection scope of the present invention is not limited thereto.

[0027] The invention relates to a group abnormal behavior identification method, which includes the following steps.

[0028] Step 1: Get the video stream.

[0029] Step 2: Perform serial pedestrian detection based on the video stream; if there are multiple people, go to the next step, otherwise, repeat step 2.

[0030] Described step 2 comprises the following steps:

[0031] Step 2.1: Process the video stream to obtain the foreground binary image;

[0032] Step 2.2: Perform connected domain detection on the foreground binary image to obtain white pixels representing pedestrians;

[0033] Step 2.3: Calculate the crowd density C, Among them, p white Indicates the white pixel in the foreground binary image, p sum Indicates the number of total pixels in the monitoring area;

[0034] Step 2.4: W...

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Abstract

The invention relates to a group abnormal behavior identification method, which is used for carrying out series pedestrian detection on the basis of an acquired video stream, calculating an energy value E on the basis of a motion history graph when multiple persons are judged, judging that multiple persons have abnormal behaviors when E is greater than or equal to a set energy threshold, and giving an alarm. From the overall perspective, significant features for distinguishing abnormal behaviors and normal behaviors are found for analysis and judgment, and the normal behaviors and the abnormalbehaviors of the group are distinguished in combination with crowd density estimation and the energy value of the motion history graph, and the accuracy of the recognition algorithm is high, and thereal-time requirement of the system is met.

Description

technical field [0001] The present invention relates to the technical field of data identification; data representation; record carrier; record carrier processing, and in particular to a group abnormal behavior identification method. Background technique [0002] Abnormal behavior recognition methods can generally be divided into two categories, including behavior recognition methods based on model matching and behavior recognition methods based on similarity measures. [0003] The model-based behavior recognition method is to extract the shape, feature points, optical flow and other information of the moving target from the video sequence containing human behavior, such as walking, jumping, running, falling, etc., for artificial modeling as a reference for known behavior Model, and then match and classify the behavior in the video with the known model to achieve the purpose of behavior recognition; the commonly used models for manual modeling include the hidden Markov model...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V20/42G06V20/49G06V20/53G06V20/46
Inventor 李文书
Owner 杭州视鑫科技有限公司
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