首页|Real-Time Safety Behavior Detection Technology of Indoors Power Personnel Based on Human Key Points

Real-Time Safety Behavior Detection Technology of Indoors Power Personnel Based on Human Key Points

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Safety production is of great significance to the development of enterprises and society.Accidents often cause great losses because of the particularity environment of electric power.Therefore,it is important to improve the safety supervision and protection in the electric power environment.In this paper,we simulate the actual electric power operation scenario by monitoring equipment and propose a real-time detection method of illegal actions based on human body key points to ensure safety behavior in real time.In this method,the human body key points in video frames were first extracted by the high-resolution network,and then classified in real time by spatial-temporal graph convolutional network.Experimental results show that this method can effectively detect illegal actions in the simulated scene.

real-time behavior recognitionhuman key pointshigh-resolution networkspatial-temporal graph convolutional network

杨坚、李聪敏、洪道鉴、卢东祁、林秋佳、方兴其、喻谦、张乾

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State Grid Zhejiang Taizhou Power Supply Company,Taizhou 318000,Zhejiang,China

Department of Automation,Shanghai Jiao Tong University,Shanghai 200240,China

Zhejiang Huayun Information Technology Co.,Ltd.,Hangzhou 310012,China

Science and Technology Program of State Grid Corporation of China

5211TZ1900S6

2024

上海交通大学学报(英文版)
上海交通大学

上海交通大学学报(英文版)

影响因子:0.151
ISSN:1007-1172
年,卷(期):2024.29(2)
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