Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning Data
The registration of bridge point cloud data (PCD) is an important preprocessing step for tasks such as bridge modeling, deformation detection, and bridge health monitoring. However, most existing research on bridge PCD registration only focused on pairwise registration, and payed insufficient attent...
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| Format: | Article |
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MDPI AG
2024-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/5/1394 |
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| author | Guikai Xiong Na Cui Jiepeng Liu Yan Zeng Hanxin Chen Chengliang Huang Hao Xu |
| author_facet | Guikai Xiong Na Cui Jiepeng Liu Yan Zeng Hanxin Chen Chengliang Huang Hao Xu |
| author_sort | Guikai Xiong |
| collection | DOAJ |
| description | The registration of bridge point cloud data (PCD) is an important preprocessing step for tasks such as bridge modeling, deformation detection, and bridge health monitoring. However, most existing research on bridge PCD registration only focused on pairwise registration, and payed insufficient attention to multi-view registration. In addition, to recover the overlaps of unordered multiple scans and obtain the merging order, extensive pairwise matching and the creation of a fully connected graph of all scans are often required, resulting in low efficiency. To address these issues, this paper proposes a marker-free template-guided method to align multiple unordered bridge PCD to a global coordinate system. Firstly, by aligning each scan to a given registration template, the overlaps between all the scans are recovered. Secondly, a fully connected graph is created based on the overlaps and scanning locations, and then a graph-partition algorithm is utilized to construct the scan-blocks. Then, the coarse-to-fine registration is performed within each scan-block, and the transformation matrix of coarse registration is obtained using an intelligent optimization algorithm. Finally, global block-to-block registration is performed to align all scans to a unified coordinate reference system. We tested our framework on different bridge point cloud datasets, including a suspension bridge and a continuous rigid frame bridge, to evaluate its accuracy. Experimental results demonstrate that our method has high accuracy. |
| first_indexed | 2024-04-25T00:20:30Z |
| format | Article |
| id | doaj.art-d6e0692d4e4c4dd8938484f6fbc3887a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-25T00:20:30Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d6e0692d4e4c4dd8938484f6fbc3887a2024-03-12T16:54:37ZengMDPI AGSensors1424-82202024-02-01245139410.3390/s24051394Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning DataGuikai Xiong0Na Cui1Jiepeng Liu2Yan Zeng3Hanxin Chen4Chengliang Huang5Hao Xu6Key Laboratory of New Technology for Construction of Cities in Mountain Area (Ministry of Education), Chongqing University, Chongqing 400045, ChinaKey Laboratory of New Technology for Construction of Cities in Mountain Area (Ministry of Education), Chongqing University, Chongqing 400045, ChinaKey Laboratory of New Technology for Construction of Cities in Mountain Area (Ministry of Education), Chongqing University, Chongqing 400045, ChinaKey Laboratory of New Technology for Construction of Cities in Mountain Area (Ministry of Education), Chongqing University, Chongqing 400045, ChinaChongqing Academy of Surveying and Mapping, Chongqing 401121, ChinaChongqing Academy of Surveying and Mapping, Chongqing 401121, ChinaSchool of Civil Engineering, Chongqing University, Chongqing 400045, ChinaThe registration of bridge point cloud data (PCD) is an important preprocessing step for tasks such as bridge modeling, deformation detection, and bridge health monitoring. However, most existing research on bridge PCD registration only focused on pairwise registration, and payed insufficient attention to multi-view registration. In addition, to recover the overlaps of unordered multiple scans and obtain the merging order, extensive pairwise matching and the creation of a fully connected graph of all scans are often required, resulting in low efficiency. To address these issues, this paper proposes a marker-free template-guided method to align multiple unordered bridge PCD to a global coordinate system. Firstly, by aligning each scan to a given registration template, the overlaps between all the scans are recovered. Secondly, a fully connected graph is created based on the overlaps and scanning locations, and then a graph-partition algorithm is utilized to construct the scan-blocks. Then, the coarse-to-fine registration is performed within each scan-block, and the transformation matrix of coarse registration is obtained using an intelligent optimization algorithm. Finally, global block-to-block registration is performed to align all scans to a unified coordinate reference system. We tested our framework on different bridge point cloud datasets, including a suspension bridge and a continuous rigid frame bridge, to evaluate its accuracy. Experimental results demonstrate that our method has high accuracy.https://www.mdpi.com/1424-8220/24/5/1394point cloud registrationhierarchical multi-view registrationterrestrial laser scanningtemplate-guidedbridge point cloud data |
| spellingShingle | Guikai Xiong Na Cui Jiepeng Liu Yan Zeng Hanxin Chen Chengliang Huang Hao Xu Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning Data Sensors point cloud registration hierarchical multi-view registration terrestrial laser scanning template-guided bridge point cloud data |
| title | Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning Data |
| title_full | Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning Data |
| title_fullStr | Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning Data |
| title_full_unstemmed | Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning Data |
| title_short | Template-Guided Hierarchical Multi-View Registration Framework of Unordered Bridge Terrestrial Laser Scanning Data |
| title_sort | template guided hierarchical multi view registration framework of unordered bridge terrestrial laser scanning data |
| topic | point cloud registration hierarchical multi-view registration terrestrial laser scanning template-guided bridge point cloud data |
| url | https://www.mdpi.com/1424-8220/24/5/1394 |
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