Abnormal behavior real-time monitoring method based on deep learning

A technology of deep learning and behavior, applied in the field of monitoring, can solve problems such as untimely processing of events, difficulty in monitoring video data analysis, and under-reporting of abnormal behaviors in monitoring video, achieving the effects of high accuracy, high cost performance, and easy operation

Inactive Publication Date: 2020-02-11
BEIJING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0015] The present invention mainly solves the technical problems that traditional video monitoring not only requires a lot of monitoring personnel, but also may have a series of problems, such as difficulty in monitoring video data analysis, missed reporting of abnormal behavior in monitoring video, untimely handling of events, etc., and proposes a method based on The real-time monitoring method of abnormal behavior of deep learning, this method uses the camera to capture the movement of the crowd within the monitoring range, input it to the core controller to judge the behavior of people, if it is judged as abnormal behavior such as chasing and fighting, it will be transmitted to the central control room or At the security office, if there is a horn, it can also be prompted through the horn

Method used

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  • Abnormal behavior real-time monitoring method based on deep learning
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  • Abnormal behavior real-time monitoring method based on deep learning

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Embodiment 1

[0082] like figure 1 As shown, Embodiment 1 of the present invention provides a method for real-time monitoring of abnormal behavior based on deep learning, including:

[0083] Step 1. Obtain video data of the human target through the camera;

[0084] Place the camera in a suitable position to obtain the video data of the human body target.

[0085] Step 2. Extract the video data of the human body target frame by frame according to the interception frequency to obtain the image of the human body target, and input the image of the human body target into the core controller OpenPose;

[0086] The image is intercepted every 10 frames from the short video captured by the camera (the interception frequency can be adjusted according to the computing resources), and input to the core processor.

[0087]Input the human target image to the core controller OpenPose, including: first adjust the size and resolution of the human target image according to the computing resources, for exam...

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Abstract

The invention provides an abnormal behavior real-time monitoring method based on deep learning. The abnormal behavior real-time monitoring method comprises the steps of obtaining human body target video data through a camera; extracting the human body target video data frame by frame according to the interception frequency to obtain a human body target image, and inputting the human body target image into a core controller; enabling a core controller to extract body key points and a skeleton structure of the human body target image, perform cascade connection on the extracted body key points of each target according to a motion time sequence to obtain a body posture evolution graph, and input the body posture evolution graph into a classifier; wherein the classifier is based on a body posture evolution diagram; distinguishing action classification to acquire target actions. An artificial intelligence algorithm is applied to a traditional video monitoring system, improvement of functions and performance is obtained, classification information of actions can be rapidly generated, the state of a human body can be well fed back, and the abnormal behaviors of the human body are corrected and supervised.

Description

technical field [0001] The invention relates to the technical field of monitoring, and relates to a method for real-time monitoring of abnormal behavior based on deep learning. Background technique [0002] Video surveillance system plays an increasingly important role in production and life, and has become an indispensable safety barrier in people's life. Banks, shopping malls, schools, communities, factories, public transportation and other public areas have great needs for video surveillance. It goes without saying that with the construction of a safe city, the monitoring system will also play its role. [0003] Many people have poor safety awareness, and accidental injuries are prone to accidents in the process of chasing and fighting. The torment of pain, even disability, harm and damage to oneself, others, and social relations or social order, and bring certain legal consequences. In particular, fighting will be extremely tempting and corrosive to minors who are not ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/06G06N3/08
CPCG06N3/084G06N3/061G06V40/20G06V20/52G06N3/045G06F18/241
Inventor 吴铭张闯刘泽萱
Owner BEIJING UNIV OF POSTS & TELECOMM
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