Surface reconstruction from arbitrarily large point clouds
Autor(en): | Wiemann, T. Mitschke, I. Mock, A. Hertzberg, J. |
Stichwörter: | Digital storage; High resolution data; Map generation; Partial results; Point cloud; Point cloud data; Point cloud processing; Robotic maps; Robotics, Consistent reconstruction; Surface reconstruction; Terrestrial laser scanning, Surface reconstruction | Erscheinungsdatum: | 2018 | Herausgeber: | Institute of Electrical and Electronics Engineers Inc. | Journal: | Proceedings - 2nd IEEE International Conference on Robotic Computing, IRC 2018 | Volumen: | 2018-January | Startseite: | 278 | Seitenende: | 281 | Zusammenfassung: | Generating 3D robotic maps from point cloud data is an active field of research. To handle high resolution data from terrestrial laser scanning to generate maps for mobile robots is still challenging, especially for city scale environments. In this short paper, we present the results of an approach for surface reconstruction from arbitrarily large point clouds. To achieve this, we serialize the large input data into suitable chunks, that are serialized to a shared hard drive. After computation, the partial results are fused into a globally consistent reconstruction. © 2018 IEEE. |
Beschreibung: | Conference of 2nd IEEE International Conference on Robotic Computing, IRC 2018 ; Conference Date: 31 January 2018 Through 2 February 2018; Conference Code:135734 |
ISBN: | 9781538646519 | DOI: | 10.1109/IRC.2018.00059 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049617079&doi=10.1109%2fIRC.2018.00059&partnerID=40&md5=d38538a6ac3d8b6882873a3b0613bc23 |
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geprüft am 01.06.2024