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 inInternational journal of digital earth Vol. 13; no. 12; pp. 1585 - 1603
Main Authors Dai, Wenxia, Yang, Bisheng, Liang, Xinlian, Dong, Zhen, Huang, Ronggang, Wang, Yunsheng, Pyörälä, Jiri, Kukko, Antero
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 01.12.2020
Taylor & Francis Ltd
Taylor & Francis Group
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ISSN1753-8947
1753-8955
1753-8955
DOI10.1080/17538947.2020.1764118

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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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ISSN:1753-8947
1753-8955
1753-8955
DOI:10.1080/17538947.2020.1764118