Hazardous chemical substance transport vehicle illegal driving behavior detection method and system based on visual collaboration

Abstract

The invention discloses a hazardous chemical transport vehicle illegal driving behavior detection method and system based on visual collaboration. The method comprises the steps that firstly, a data set is made, and image enhancement and normalization processing are carried out; marking dangerous driving behavior sensitive articles, and training the data set for the sensitive articles through a target recognition neural network; reading each frame of the video, detecting a sensitive object through the trained network model, and then performing human body posture key point detection on the frames; coordinate positions of the left and right hand key points in the frame image are obtained through human body posture detection, position information of the key points and the sensitive object recognition frame is judged, and corresponding illegal driving behaviors are recognized; and early warning is performed when the continuous time window of the illegal driving behavior exceeds a set threshold, and the video clip is reserved. The method can adapt to real-time detection and early warning of dangerous driving behaviors of a driver in a monitoring video, facilitates the timely discovery and prompt of non-standard driving behaviors, reduces the occurrence of traffic accidents, is various in detection types, and is good in recognition effect.

Description

technical field [0001] The invention relates to the fields of image processing and traffic safety, in particular to a method and system for detecting illegal driving behavior of a hazardous chemical transport vehicle based on visual collaboration. Background technique [0002] With the rapid development of social economy, the market scale of chemical industry products is growing day by day, becoming the foundation of the national economy. According to research data, the scale of my country's hazardous chemicals market reached 1.4 trillion in 2018, and this scale will continue to expand in the future. According to the spirit of the "Opinions of the Central Committee of the Communist Party of China and the State Council on Promoting Reform and Development in the Field of Safety Production" (Zhongfa [2016] No. 32) issued on December 18, 2016, Jiangsu Province issued two red-headed documents in succession. Both documents also require the mandatory installation of anti-collision...

AI Technical Summary

Problems solved by technology

[0004] These commonly used video behavior detection techniques are effective ideas for processing traffic video big data, but there is no behavior-specific processing for video surveillance of drivers of hazardous chemical transport vehicles, and it is impossible to identify dangerous driving behaviors of drivers and sensitive items. , so it is impossible to comprehensively identify the driver's dangerous driving behavior

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