Human 3D pose estimation in a lying position by RGB-D images for medical diagnosis and rehabilitation
Qingqiang Wu, Guanghua Xu, Sicong Zhang, Yu Li, Wei Fan · 2020
Posture recognition in the human lying position is of great significance for the rehabilitation evaluation of lying patients and the diagnosis of infants with early cerebral palsy. In this paper, we proposed a novel method for human 3D pose estimation in a lying position with the RGB image and corresponding depth information. Firstly, we employ current pose estimation method on RGB images to achieve the human full body 2D keypoints. By combining the depth information and coordinate transformation, the 3D movement of human in lying position can be obtained. We validate our method with two public datasets. The results show that the accuracy can reach the state-of-the-art.