Wu Qingqiang, Xu Guanghua, Zhang Sicong, Li Yu, Wei Fan
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:5802-5805. doi: 10.1109/EMBC44109.2020.9176407.
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.
人体卧位姿势识别对于卧位患者的康复评估以及早期脑瘫婴儿的诊断具有重要意义。在本文中，我们提出了一种利用RGB图像和相应深度信息进行人体卧位3D姿态估计的新方法。首先，我们采用当前的RGB图像姿态估计方法来获取人体全身2D关键点。通过结合深度信息和坐标变换，可以得到人体卧位时的3D运动。我们使用两个公共数据集对我们的方法进行了验证。结果表明，该方法的准确率可以达到当前最优水平。
