Fast registration of forest terrestrial laser scans using key points detected from crowns and stems
Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. Most existing registration methods rely on stems to determine the transformation parameters. However, the complexity of the registration problem increases dramatically as the number of stems grows. It is...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-12-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17538947.2020.1764118 |
| _version_ | 1827811147729862656 |
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| author | Wenxia Dai Bisheng Yang Xinlian Liang Zhen Dong Ronggang Huang Yunsheng Wang Jiri Pyörälä Antero Kukko |
| author_facet | Wenxia Dai Bisheng Yang Xinlian Liang Zhen Dong Ronggang Huang Yunsheng Wang Jiri Pyörälä Antero Kukko |
| author_sort | Wenxia Dai |
| collection | DOAJ |
| description | Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. Most existing registration methods rely on stems to determine the transformation parameters. However, the complexity of the registration problem increases dramatically as the number of stems grows. It is tricky to reduce the stems and determine the valid ones that can provide reliable registration transformation without a knowledge of the two scans. This paper presents an automatic and fast registration of TLS point clouds in forest areas. It reduces stems by selecting from the overlap areas, which are recovered from the mode-based key points that are detected from crowns. The proposed method was tested in a managed forest in Finland, and was compared with the stem-based registration method without reducing stems. The experiments demonstrated that the mean rotation error was 2.09′, and the mean errors in horizontal and vertical translation were 1.13 and 7.21 cm, respectively. Compared with the stem-based method, the proposed method improves the registration efficiency significantly (818 s vs 96 s) and achieves similar results in terms of the mean registration errors (1.94′ for rotation error, 0.83 and 7.38 cm for horizontal and vertical translation error, respectively). |
| first_indexed | 2024-03-11T23:01:03Z |
| format | Article |
| id | doaj.art-ee1433a29c32453382ced233e1c568d1 |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-11T23:01:03Z |
| publishDate | 2020-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-ee1433a29c32453382ced233e1c568d12023-09-21T14:57:09ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552020-12-0113121585160310.1080/17538947.2020.17641181764118Fast registration of forest terrestrial laser scans using key points detected from crowns and stemsWenxia Dai0Bisheng Yang1Xinlian Liang2Zhen Dong3Ronggang Huang4Yunsheng Wang5Jiri Pyörälä6Antero Kukko7State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan UniversityState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan UniversityDepartment of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, FGI (Former Finnish Geodetic Institute)State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan UniversityInstitute of Geodesy and Geophysics, Chinese Academy of SciencesDepartment of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, FGI (Former Finnish Geodetic Institute)Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, FGI (Former Finnish Geodetic Institute)Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, FGI (Former Finnish Geodetic Institute)Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. Most existing registration methods rely on stems to determine the transformation parameters. However, the complexity of the registration problem increases dramatically as the number of stems grows. It is tricky to reduce the stems and determine the valid ones that can provide reliable registration transformation without a knowledge of the two scans. This paper presents an automatic and fast registration of TLS point clouds in forest areas. It reduces stems by selecting from the overlap areas, which are recovered from the mode-based key points that are detected from crowns. The proposed method was tested in a managed forest in Finland, and was compared with the stem-based registration method without reducing stems. The experiments demonstrated that the mean rotation error was 2.09′, and the mean errors in horizontal and vertical translation were 1.13 and 7.21 cm, respectively. Compared with the stem-based method, the proposed method improves the registration efficiency significantly (818 s vs 96 s) and achieves similar results in terms of the mean registration errors (1.94′ for rotation error, 0.83 and 7.38 cm for horizontal and vertical translation error, respectively).http://dx.doi.org/10.1080/17538947.2020.1764118terrestrial laser scanning (tls)forestpoint cloudsregistration |
| spellingShingle | Wenxia Dai Bisheng Yang Xinlian Liang Zhen Dong Ronggang Huang Yunsheng Wang Jiri Pyörälä Antero Kukko Fast registration of forest terrestrial laser scans using key points detected from crowns and stems International Journal of Digital Earth terrestrial laser scanning (tls) forest point clouds registration |
| title | Fast registration of forest terrestrial laser scans using key points detected from crowns and stems |
| title_full | Fast registration of forest terrestrial laser scans using key points detected from crowns and stems |
| title_fullStr | Fast registration of forest terrestrial laser scans using key points detected from crowns and stems |
| title_full_unstemmed | Fast registration of forest terrestrial laser scans using key points detected from crowns and stems |
| title_short | Fast registration of forest terrestrial laser scans using key points detected from crowns and stems |
| title_sort | fast registration of forest terrestrial laser scans using key points detected from crowns and stems |
| topic | terrestrial laser scanning (tls) forest point clouds registration |
| url | http://dx.doi.org/10.1080/17538947.2020.1764118 |
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