Aiming at the high requirements of existing fall detection equipment based on human skeleton,a fall detection method based on lightweight OpenPose generating skeleton features is proposed.Firstly,the keypoints of the human body are detected based on the lightweight OpenPose network.The partial keypoints of the human are used to generate the bounding box,and the coordinates of the keypoints are normalized processing.The aspect ratio of the bounding box and the standardized keypoints coordinates as feature vectors representing human pose.Finally,the human body pose feature vector is used as the input of the multilayer perceptron(MLP)to determine whether the human body falls or not.The experimental results show that the network can achieve fall detection accuracy rate of 98.64% based on the customed fall dataset constructed by the images collected by the monocular camera and can achieve a detection speed of 20 fps on the CoreTMi5-9300H CPU.
维普
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