Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/91944
Title: | Pairwise point cloud registration using graph matching and rotation-invariant features | Authors: | Huang, R Yao, W Xu, Y Ye, Z Stilla, U |
Issue Date: | 2022 | Source: | IEEE geoscience and remote sensing letters, 2021, v. 19, 6502805, p. 1-5 | Abstract: | Registration is a fundamental but critical task in point cloud processing, which usually depends on finding element correspondence from two point clouds. However, the finding of reliable correspondence relies on establishing a robust and discriminative description of elements and the correct matching of corresponding elements. In this letter, we develop a coarse-to-fine registration strategy, which utilizes rotation-invariant features in frequency domain and a new graph matching (GM) method for iteratively searching correspondence. In the GM method, the similarity of both nodes and edges in the Euclidean and feature space is formulated to construct the optimization function. The proposed strategy is evaluated using two benchmark datasets and compared with several state-of-the-art methods. Regarding the experimental results, our proposed method can achieve a fine registration with rotation errors of less than 0.2° and translation errors of less than 0.1 m. | Keywords: | Transforms 3-D descriptor Graph matching (GM) Point cloud registration Rotation invariance |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE geoscience and remote sensing letters | ISSN: | 1545-598X | DOI: | 10.1109/LGRS.2021.3109470 | Rights: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for Publishedertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication R. Huang, W. Yao, Y. Xu, Z. Ye and U. Stilla, "Pairwise Point Cloud Registration Using Graph Matching and Rotation-Invariant Features," in IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 6502805 is available at https://dx.doi.org/10.1109/LGRS.2021.3109470. |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Huang_Pairwise_Point_Cloud.pdf | Pre-Published version | 7.37 MB | Adobe PDF | View/Open |
Page views
35
Last Week
0
0
Last month
Citations as of May 28, 2023
Downloads
1
Citations as of May 28, 2023
SCOPUSTM
Citations
3
Citations as of May 25, 2023
WEB OF SCIENCETM
Citations
5
Citations as of May 25, 2023

Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.