3D keypoint detection of lying human body is important to improve the efficiency of mobile rescue robots at the casualty collection point after a disaster (e.g., earthquake and mudslide). In this paper, we propose an efficient method for 3D human keypoint detection in a lying posture using an RGB-D camera. First, we use the current 2D human pose estimation algorithm for RGB images to obtain 2D keypoints of the whole body. We then obtain the final 3D coordinates of the human keypoint by processing the 2D coordinates through a filter of our design and combining the depth information with a coordinate transformation. Experiments show that the proposed method is accurate and fast enough to be used for 3D keypoint detection of lying human body by the mobile rescue robot at the casualty collection point.
JiGwan ParkKijin AnJongSuk Choi
Alexander V. FisunovVictoria B. Gnezdilova
Cristina Romero-GonzálezJesús Martínez-GómezIsmael García-VareaLuis Rodríguez-Ruiz