A Fast Registration Method for Building Point Clouds Obtained by Terrestrial Laser Scanner via 2-D Feature Points
Point cloud registration plays a central role in various applications, such as 3-D scene reconstruction, preservation of cultural heritage and deformation monitoring. The point cloud data are usually huge. Processing such huge data is very time-consuming, so a fast and accurate registration method i...
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IEEE
2024-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10508065/ |
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| author | Wuyong Tao Yansheng Xiao Ruisheng Wang Tieding Lu Shaoping Xu |
| author_facet | Wuyong Tao Yansheng Xiao Ruisheng Wang Tieding Lu Shaoping Xu |
| author_sort | Wuyong Tao |
| collection | DOAJ |
| description | Point cloud registration plays a central role in various applications, such as 3-D scene reconstruction, preservation of cultural heritage and deformation monitoring. The point cloud data are usually huge. Processing such huge data is very time-consuming, so a fast and accurate registration method is crucial. However, the existing registration methods still have high computation complexity or low accuracy. To address this issue, we develop a registration method for terrestrial point clouds. The method projects the point clouds onto the horizontal plane. Therefore, our method processes point cloud data in 2-D space, leading to high computation efficiency. Then, the 2-D feature lines are extracted from the projected point clouds. We calculate the intersection points of the 2-D feature lines, which are treated as the 2-D feature points. Due to the high accuracy of the 2-D feature lines, the 2-D feature points also have high accuracy. Thus, our method can get accurate registration results. Afterward, the feature triangles are constructed by using the 2-D feature points, and the geometric constraints are utilized to find the corresponding feature triangles for calculating the 2-D transformation. This strategy boosts the process of searching for the corresponding 2-D feature points. Subsequently, the <italic>Z</italic>-axis displacement is computed by the cylindrical neighborhoods. By combining the <italic>Z</italic>-axis displacement and 2-D transformation, the 3-D rigid transformation is obtained. Experimental evaluation conducted on two publicly available datasets well demonstrates that the proposed registration method can achieve good computational efficiency and high accuracy. |
| format | Article |
| id | doaj-art-3a3a19b53f2e45e5a1dcab0c73658367 |
| institution | DOAJ |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-3a3a19b53f2e45e5a1dcab0c736583672025-08-20T02:52:27ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352024-01-01179324933610.1109/JSTARS.2024.339292710508065A Fast Registration Method for Building Point Clouds Obtained by Terrestrial Laser Scanner via 2-D Feature PointsWuyong Tao0https://orcid.org/0000-0003-0821-644XYansheng Xiao1Ruisheng Wang2https://orcid.org/0000-0003-0745-5158Tieding Lu3Shaoping Xu4https://orcid.org/0000-0003-0628-334XSchool of Mathematics and Computer Sciences, Nanchang University, Nanchang, ChinaSchool of Mathematics and Computer Sciences, Nanchang University, Nanchang, ChinaSchool of Architecture & Urban Planning, Shenzhen University, Shenzhen, ChinaLaboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang, ChinaSchool of Mathematics and Computer Sciences, Nanchang University, Nanchang, ChinaPoint cloud registration plays a central role in various applications, such as 3-D scene reconstruction, preservation of cultural heritage and deformation monitoring. The point cloud data are usually huge. Processing such huge data is very time-consuming, so a fast and accurate registration method is crucial. However, the existing registration methods still have high computation complexity or low accuracy. To address this issue, we develop a registration method for terrestrial point clouds. The method projects the point clouds onto the horizontal plane. Therefore, our method processes point cloud data in 2-D space, leading to high computation efficiency. Then, the 2-D feature lines are extracted from the projected point clouds. We calculate the intersection points of the 2-D feature lines, which are treated as the 2-D feature points. Due to the high accuracy of the 2-D feature lines, the 2-D feature points also have high accuracy. Thus, our method can get accurate registration results. Afterward, the feature triangles are constructed by using the 2-D feature points, and the geometric constraints are utilized to find the corresponding feature triangles for calculating the 2-D transformation. This strategy boosts the process of searching for the corresponding 2-D feature points. Subsequently, the <italic>Z</italic>-axis displacement is computed by the cylindrical neighborhoods. By combining the <italic>Z</italic>-axis displacement and 2-D transformation, the 3-D rigid transformation is obtained. Experimental evaluation conducted on two publicly available datasets well demonstrates that the proposed registration method can achieve good computational efficiency and high accuracy.https://ieeexplore.ieee.org/document/10508065/Point cloud registrationcongruent feature triangle2-D feature point2-D transformation |
| spellingShingle | Wuyong Tao Yansheng Xiao Ruisheng Wang Tieding Lu Shaoping Xu A Fast Registration Method for Building Point Clouds Obtained by Terrestrial Laser Scanner via 2-D Feature Points IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Point cloud registration congruent feature triangle 2-D feature point 2-D transformation |
| title | A Fast Registration Method for Building Point Clouds Obtained by Terrestrial Laser Scanner via 2-D Feature Points |
| title_full | A Fast Registration Method for Building Point Clouds Obtained by Terrestrial Laser Scanner via 2-D Feature Points |
| title_fullStr | A Fast Registration Method for Building Point Clouds Obtained by Terrestrial Laser Scanner via 2-D Feature Points |
| title_full_unstemmed | A Fast Registration Method for Building Point Clouds Obtained by Terrestrial Laser Scanner via 2-D Feature Points |
| title_short | A Fast Registration Method for Building Point Clouds Obtained by Terrestrial Laser Scanner via 2-D Feature Points |
| title_sort | fast registration method for building point clouds obtained by terrestrial laser scanner via 2 d feature points |
| topic | Point cloud registration congruent feature triangle 2-D feature point 2-D transformation |
| url | https://ieeexplore.ieee.org/document/10508065/ |
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