An analytical approach to evaluate point cloud registration error utilizing targets

Yang, Ronghua; Meng, Xiaolin; Yao, Yibin; Chen, Bi Yu; You, Yangsheng; Xiang, Zejun

Abstract

Point cloud registration is essential for processing terrestrial laser scanning (TLS) point cloud datasets. The registration precision directly influences and determines the practical usefulness of TLS surveys. However, in terms of target based registration, analytical point cloud registration error models employed by scanner manufactures are only suitable to evaluate target registration error, rather than point cloud registration error. This paper proposes an new analytical approach called the registration error (RE) model to directly evaluate point cloud registration error. We verify the proposed model by comparing RE and root mean square error (RMSE) for all points in three point clouds that are approximately equivalent.

Citation

Yang, R., Meng, X., Yao, Y., Chen, B. Y., You, Y., & Xiang, Z. (2018). An analytical approach to evaluate point cloud registration error utilizing targets. ISPRS Journal of Photogrammetry and Remote Sensing, 143, 48-56. https://doi.org/10.1016/j.isprsjprs.2018.05.002

• Journal Article Type: Article
• Acceptance Date: May 8, 2018
• Online Publication Date: Jun 22, 2018
• Publication Date: Sep 30, 2018
• Deposit Date: Jan 26, 2019
• Publicly Available Date: Jun 23, 2019
• Journal: ISPRS Journal of Photogrammetry and Remote Sensing
• Print ISSN: 0924-2716
• Electronic ISSN: 0924-2716
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 143
• Pages: 48-56
• DOI: https://doi.org/10.1016/j.isprsjprs.2018.05.002
• Keywords: Computers in Earth Sciences; Engineering (miscellaneous); Atomic and Molecular Physics, and Optics; Computer Science Applications
• Public URL: https://nottingham-repository.worktribe.com/output/1498289
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0924271618301369?via%3Dihub
• Contract Date: Jan 26, 2019