Print Email Facebook Twitter GlobalMatch Title GlobalMatch: Registration of forest terrestrial point clouds by global matching of relative stem positions Author Wang, Xufei (Tongji University) Yang, Z. (TU Delft Urban Data Science; Tongji University) Cheng, Xiaojun (Tongji University) Stoter, J.E. (TU Delft Urban Data Science) Xu, Wenbing (Zhejiang Agriculture and Forestry University) Wu, Zhenlun (Big Data Development Administration of Yichun) Nan, L. (TU Delft Urban Data Science) Date 2023 Abstract Registering point clouds of forest environments is an essential prerequisite for LiDAR applications in precision forestry. State-of-the-art methods for forest point cloud registration require the extraction of individual tree attributes, and they have an efficiency bottleneck when dealing with point clouds of real-world forests with dense trees. We propose an automatic, robust, and efficient method for the registration of forest point clouds. Our approach first locates tree stems from raw point clouds and then matches the stems based on their relative spatial relationship to determine the registration transformation. The algorithm requires no extra individual tree attributes and has quadratic complexity to the number of trees in the environment, allowing it to align point clouds of large forest environments. Extensive experiments on forest terrestrial point clouds have revealed that our method inherits the effectiveness and robustness of the stem-based registration strategy while exceedingly increasing its efficiency. Besides, we introduce a new benchmark dataset that complements the very few existing open datasets for the development and evaluation of registration methods for forest point clouds. The source code of our method and the dataset are available at https://github.com/zexinyang/GlobalMatch. Subject DatasetForestLaser scanningPoint cloudRegistration To reference this document use: http://resolver.tudelft.nl/uuid:2cd2f7a0-7f1a-47da-84c6-d627b21e5502 DOI https://doi.org/10.1016/j.isprsjprs.2023.01.013 Embargo date 2023-08-01 ISSN 0924-2716 Source ISPRS Journal of Photogrammetry and Remote Sensing, 197, 71-86 Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2023 Xufei Wang, Z. Yang, Xiaojun Cheng, J.E. Stoter, Wenbing Xu, Zhenlun Wu, L. Nan Files PDF 1_s2.0_S0924271623000199_main.pdf 6.06 MB Close viewer /islandora/object/uuid:2cd2f7a0-7f1a-47da-84c6-d627b21e5502/datastream/OBJ/view