The proposed fall detection approach is aimed at building a support system for the elders. In this work, a method based on human pose estimation and lightweight neural network is used to detect falls. First, the OpenPose is used to extract human keypoints and label them in the images. After that, the modified MobileNetV2 network is used to detect falls by integrating both human keypoint information and pose information in the original images. The above operation can use the original image information to correct the deviation in the keypoint labeling process. Through experiments, the accuracy of the proposed method is 98.6% and 99.75% on the UR and Le2i datasets, which is higher than the listed comparison methods.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.