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An analytical approach to evaluate point cloud registration error utilizing targets

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


Ronghua Yang

Xiaolin Meng

Yibin Yao

Bi Yu Chen

Yangsheng You

Zejun Xiang


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.


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. doi: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
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 143
Pages 48-56
Keywords Computers in Earth Sciences; Engineering (miscellaneous); Atomic and Molecular Physics, and Optics; Computer Science Applications
Public URL
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