@inproceedings{a80b73cf61f248e8bfc4125383b04851,
title = "3D Keypoint Detection of Lying Human Body Using an RGB-D Camera",
abstract = "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.",
keywords = "Deep Learning, Human Keypoint Detection, Mobile Rescue Robot, RGB-D",
author = "Zezheng Qi and Yunjiang Lou",
note = "Publisher Copyright: {\textcopyright} 2023 Technical Committee on Control Theory, Chinese Association of Automation.; 42nd Chinese Control Conference, CCC 2023 ; Conference date: 24-07-2023 Through 26-07-2023",
year = "2023",
doi = "10.23919/CCC58697.2023.10240563",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "7459--7464",
booktitle = "2023 42nd Chinese Control Conference, CCC 2023",
address = "美国",
}