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Titel:

Refinement of semantic 3D building models by reconstructing underpasses from MLS point clouds

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Wysocki, Olaf; Hoegner, Ludwig; Stilla, Uwe
Abstract:
Semantic 3D building models are provided by public authorities and can be used in applications, such as urban planning, simulations, navigation, and many others. Since large-scale 3D models are typically derived from top-view digital surface models (DSM), they can have detailed roof structures but render planes for façade elements. Furthermore, buildings’ underpasses are often unmodeled, which impacts road space modeling and the building’s volume score. For refining semantic 3D building models,...     »
Stichworte:
MLS point clouds, Building reconstruction, Semantic 3D building models, Underpasses, Buildings refinement, Bayesian networks, Uncertainty, LOCenter, LOCTop_Data_Generation_and_Object_Reconstruction
Zeitschriftentitel:
International Journal of Applied Earth Observation and Geoinformation
Jahr:
2022
Band / Volume:
111
Seitenangaben Beitrag:
102841
Volltext / DOI:
doi:https://doi.org/10.1016/j.jag.2022.102841
WWW:
https://www.sciencedirect.com/science/article/pii/S1569843222000437
Print-ISSN:
1569-8432
Semester:
SS 22
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