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Title	Progress And Perspectives Of Point Cloud Intelligence
ID_Doc	43360
Authors	Yang B.; Haala N.; Dong Z.
Year	2023
Published	Geo-Spatial Information Science, 26, 2
DOI	http://dx.doi.org/10.1080/10095020.2023.2175478
Abstract	With the rapid development of reality capture methods, such as laser scanning and oblique photogrammetry, point cloud data have become the third most important data source, after vector maps and imagery. Point cloud data also play an increasingly important role in scientific research and engineering in the fields of Earth science, spatial cognition, and smart cities. However, how to acquire high-quality three-dimensional (3D) geospatial information from point clouds has become a scientific frontier, for which there is an urgent demand in the fields of surveying and mapping, as well as geoscience applications. To address the challenges mentioned above, point cloud intelligence came into being. This paper summarizes the state-of-the-art of point cloud intelligence, with regard to acquisition equipment, intelligent processing, scientific research, and engineering applications. For this purpose, we refer to a recent project on the hybrid georeferencing of images and LiDAR data for high-quality point cloud collection, as well as a current benchmark for the semantic segmentation of high-resolution 3D point clouds. These projects were conducted at the Institute for Photogrammetry, the University of Stuttgart, which was initially headed by the late Prof. Ackermann. Finally, the development prospects of point cloud intelligence are summarized. © 2023 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group.
Author Keywords	machine learning; Point cloud big data; point cloud intelligence; semantic labeling; structured modeling

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