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...
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Published in | International journal of digital earth Vol. 13; no. 12; pp. 1585 - 1603 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Abingdon
Taylor & Francis
01.12.2020
Taylor & Francis Ltd Taylor & Francis Group |
Subjects | |
Online Access | Get full text |
ISSN | 1753-8947 1753-8955 1753-8955 |
DOI | 10.1080/17538947.2020.1764118 |
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Summary: | 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). |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1753-8947 1753-8955 1753-8955 |
DOI: | 10.1080/17538947.2020.1764118 |