3D reconstruction based on pose transformation of human joints

Song Tao; Jinshuang Li; Ruihua Liu; Siyu Duan

doi:10.1117/12.3029150

6 May 2024 3D reconstruction based on pose transformation of human joints

Song Tao, Jinshuang Li, Ruihua Liu, Siyu Duan

Proceedings Volume 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024); 131073E (2024) https://doi.org/10.1117/12.3029150
Event: Fourth International Conference on Sensors and Information Technology (ICSI 2024), 2024, Xiamen, China

Abstract

Data obtained from depth camera scans of the human body often includes noise, and registering consecutive frames can lead to errors due to inevitable non-rigid movements during scanning. To address this, we propose a method for 3D human body reconstruction based on human joint points. Initially, the Kinect DK sensor captures data from different angles, which is then preprocessed to extract the main body point cloud. Subsequently, segmented human body data, combined with pose-related joint points, guides the point cloud data of the body's surface. Using an enhanced iterative closest point algorithm, we achieve precise registration of the main body point cloud, resulting in an accurate 3D human body model. Experimental results show that this method rapidly generates realistic, finely detailed, and accurately dimensioned 3D human body models.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Song Tao, Jinshuang Li, Ruihua Liu, and Siyu Duan "3D reconstruction based on pose transformation of human joints", Proc. SPIE 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024), 131073E (6 May 2024); https://doi.org/10.1117/12.3029150

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