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

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...

AI Technical Summary

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 safety hazards

[0003] However, there are currently few methods of using video image data for sleep alerts. Generally, off-line data is acquired by sensors for sleep classification and identification. There are few methods for sleep alerts, and the range of alternative methods is narrow

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