Automatic 3D Model Registration for Global Localization based on Publicly Available Georeferenced CityGML Data

Abstract. Nowadays, there are many publicly available georeferenced data, like 3D CityGML models, that can be used as prior knowledge to perform accurate global localization. Iterative Closest Point (ICP) is a promising method for achieving this task, but it requires two point clouds that need to be partially overlapping in the initial state for better registration performance. Therefore, we investigated different detection and matching methods to automatically pre-register two non-overlapping point clouds based on a 2D overhead view and evaluated the registration results produced by an ICP algorithm. We used public data from the city of Aachen, Germany. A georeferenced point cloud was derived from the LOD2 CityGML model and a local point cloud was reconstructed from an image sequence using Structure from Motion (SFM). The evaluation results show that georeferenced LOD2 CityGML models can successfully be used for city-scale sub-meter global localization.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Automatic 3D Model Registration for Global Localization based on Publicly Available Georeferenced CityGML Data ; volume:XLVIII-4/W11-2024 ; year:2024 ; pages:65-71 ; extent:7
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVIII-4/W11-2024 (2024), 65-71 (gesamt 7)

Urheber
Liu, Zhenyu
Blut, Christoph
Blankenbach, Jörg

DOI
10.5194/isprs-archives-XLVIII-4-W11-2024-65-2024
URN
urn:nbn:de:101:1-2408061104023.867546526108
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
14.08.2025, 10:54 MESZ

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