Behavior identification method in dangerous area

A recognition method and technology of dangerous areas, applied in the field of behavior recognition in dangerous areas, can solve the problems of limited detection methods such as image feature extraction and detection effects of the camera's own conditions, to achieve rich diversity and individual differences, and a sufficient amount of data , Good effect of robustness

Pending Publication Date: 2021-06-15
中润油联天下网络科技有限公司
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a behavior recognition method in a dangerous area, which can effectively solve the problem that the existing detection method is limited by the camera's own conditions and the scene environment's detection effect on image feature extraction

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  • Behavior identification method in dangerous area
  • Behavior identification method in dangerous area

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Embodiment Construction

[0034] In order to make the objects and advantages of the present invention clearer, the present invention will be specifically described below in conjunction with examples. It should be understood that the following words are only used to describe one or several specific implementation modes of the present invention, and do not strictly limit the protection scope of the specific claims of the present invention.

[0035] In this embodiment, taking the detection of phone calls in the gas station scene as an example to illustrate the behavior recognition method in the dangerous area of ​​the present invention, the method of phone call detection in the gas station area, such as figure 1 shown, including the following steps:

[0036] (1) For the call detection in the gas station scene, it is first necessary to establish the camera area and the installation position of the camera. The installation angle will have a certain impact on the recognition of the model. Try to keep the cam...

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Abstract

The invention relates to a behavior identification method in a dangerous area, and the method comprises the following steps: obtaining video data in an actual scene, processing the video data, and arranging the video data into a training sample set which comprises a figure image and position information and category information corresponding to the figure image; training the target detection model by adopting the training sample set to obtain a trained detection model, and then taking the trained detection model as a human body detection model; when the specific position of the image corresponding to the figure is detected, cutting out the image corresponding to the figure to serve as input data of the human body detection model, thereby acquiring key point positions of all parts of the human body; and inferring the behavior characteristics of the figure according to the key point positions. According to the behavior identification method in the dangerous area provided in the technical scheme, the problem that an existing detection method is limited by the conditions of a camera and the image feature extraction detection effect of a field environment can be effectively solved.

Description

technical field [0001] The invention relates to the technical field of target detection, in particular to a behavior recognition method in a dangerous area. Background technique [0002] Call detection is a category of behavior detection, and it is also the direction for the development of artificial intelligence in the future. For the control of public places, such as gas stations, personnel supervision cannot play a real-time supervision role, or post-surveillance video screening requires a lot of Manpower and time cost and not proactive. [0003] The existing call detection technology is basically: 1. The traditional method is to extract the features of the human body, input it into the classifier, and obtain the classification model of whether to make a call; 2. CNN head detection based on deep learning to determine whether there is a call or not. phone behavior. With the vigorous development of deep learning, the behavior detection technology based on deep learning ha...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/10G06V20/41G06N3/045G06F18/214G06F18/241
Inventor 李阳陈浩许华杨大江
Owner 中润油联天下网络科技有限公司
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