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Titel:

TUM CMS Indoor point cloud

Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
22.05.2024
Verantwortlich:
Mehranfar, Mansour
Autorinnen / Autoren:
Mehranfar, Mansour; Vega-Torres, Miguel-A.; Braun, Alexander; Borrmann, André
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Identifikator:
doi:10.14459/2024mp1742891
Enddatum der Datenerzeugung:
11.01.2023
Fachgebiet:
BAU Bauingenieurwesen, Vermessungswesen; DAT Datenverarbeitung, Informatik; TEC Technik, Ingenieurwissenschaften (allgemein); UMW Umweltwissenschaften
Quellen der Daten:
Abbildungen von Objekten / image of objects; Statistik und Referenzdaten / statistics and reference data
Datentyp:
mehrdimensionale Visualisierungen oder Modelle / models
Anderer Datentyp:
Indoor point cloud data captured by laser scanner device
Methode der Datenerhebung:
The datasets were captured utilizing the NavVis VLX laser scanner (www.navvis.com).
Beschreibung:
The TUM CMS indoor dataset comprises raw RGB point cloud data captured from five distinct indoor areas within two buildings at the Technical University of Munich. These buildings primarily serve educational purposes and encompass various spaces such as offices, meeting rooms, hallways, etc. The datasets were meticulously captured utilizing the NavVis VLX laser scanner (www.navvis.com), ensuring high-quality and dense point cloud representations. This rich dataset offers significant value for res...     »
Links:
This dataset relates to the publication: https://doi.org/10.1016/j.aei.2024.102643
Schlagworte:
Point cloud; Digital Twinning; LOCenter; Built Environment; IFC; BIM
Technische Hinweise:
View and download (3.2 GB total, 8 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1742891):
rsync rsync://m1742891@dataserv.ub.tum.de/m1742891/
Sprache:
en
Rechte:
by-nc, http://creativecommons.org/licenses/by-nc/4.0
 BibTeX