Automatic detection of safety helmet wearing based on head region location

Abstract

In order to solve the problem of difficult and low precision in the detection of safety helmet wearing in the complex pose of construction worker, a detection method of safety helmet wearing based on pose estimation is proposed. In the pose estimation model of OpenPose, the residual network optimized feature extraction is introduced to obtain the skeletal point information of the construction worker, and then the pose of the construction worker is estimated based on the skeletal point information, three-point localization method is proposed for the front and back pose, and skin colour detection method is proposed for the side pose, and then to determine the head region. The YOLO v4 is used to detect the safety helmet region, and then the construction worker's safety helmet wearing is judged according to whether the head region intersects the safety helmet region or not. Experimental results show that the detection accuracy of the method is higher than other methods, and the adaptability to the environment is stronger.