Anti-off-post and anti-sleep-on-post detection method and device

A sleeping post and anti-escape technology, applied in the direction of neural learning methods, instruments, biological neural network models, etc., can solve the problems of few warning methods for sleeping posts, hidden safety hazards, and narrow range of selection methods

Pending Publication Date: 2022-02-11
湖南中科助英智能科技研究院有限公司
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Problems solved by technology

How to detect and prohibit employees from sleeping on duty has always been a question that many managers think about, because the duty room often requires employees to concentrate and stay vigilant at all times. Once the negligence caused by sleeping on duty is likely to cause huge s

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  • Anti-off-post and anti-sleep-on-post detection method and device
  • Anti-off-post and anti-sleep-on-post detection method and device
  • Anti-off-post and anti-sleep-on-post detection method and device

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Embodiment Construction

[0049] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0050] In one embodiment, such as figure 1 As shown, there is provided a kind of detection method for anti-falling and sleeping, comprising the following steps:

[0051] Step 102, acquiring the off-post sleeping video captured by the camera, and decomposing the off-post sleeping video to obtain an image frame sequence.

[0052] Decomposing the off-post and sleeping-on-post video into image frame sequences is beneficial for human body area labeling from single frame images and construction of human body area detection samples.

[0053] Step 104, labeling the human body ar...

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Abstract

The invention relates to an anti-off-post and anti-sleep-on-post detection method and device, computer equipment and a storage medium. The method comprises the following steps: training a YOLOv5x model by using a human body region detection sample, and outputting a human body region frame; extracting coordinate positions of the human body key points from the human body region frame, and obtaining a sleep-on-post skeleton space-time diagram according to the coordinate positions of the human body key points of each image frame in the image frame sequence; training a behavior prediction model through the sleep-on-post skeleton space-time diagram to obtain a trained behavior prediction model; and carrying out human body off-post detection by utilizing the trained YOLOv5x model, and if the YOLOv5x model outputs a human body region frame, carrying out sleep behavior detection on the human body according to the trained behavior prediction model. By adopting the method, the off-post and sleep-on-post behaviors can be detected.

Description

technical field [0001] The present application relates to the technical field of smart security, and in particular to a detection method, device, computer equipment and storage medium for preventing falling off and sleeping. Background technique [0002] With the in-depth application of the Internet and artificial intelligence, the work, study and life of camps are gradually moving towards intelligent integration. Smart camps use various application service systems as carriers to fully integrate teaching, scientific research, management and leisure life. How to detect and prohibit employees from sleeping on duty has always been a question that many managers think about, because the duty room often requires employees to concentrate and stay vigilant at all times. Once the negligence caused by sleeping on duty is likely to cause huge safety hazards. [0003] However, there are currently few methods of using video image data for sleep watch alarms. Generally, off-line data is a...

Claims

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Application Information

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IPC IPC(8): G06V20/40G06V40/20G06V10/22G06V10/46G06V10/82G06N3/04G06N3/08
CPCG06N3/049G06N3/08G06N3/045
Inventor 谢昌颐李蕾
Owner 湖南中科助英智能科技研究院有限公司
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