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- Titel:
TUM-FAÇADE
- Dokumenttyp:
- Forschungsdaten
- Veröffentlichungsdatum:
- 05.05.2023
- Verantwortlich:
- Wysocki, Olaf
- Autorinnen / Autoren:
- Wysocki, Olaf ; Tan, Yue; Zhang, Jiarui ; Stilla, Uwe
- Institutionszugehörigkeit:
- TUM
- Herausgeber:
- TUM
- Identifikator:
- doi:10.14459/2021mp1636761.003
- Konzept-DOI:
- doi:10.14459/2021mp1636761
- Enddatum der Datenerzeugung:
- 01.04.2023
- Fachgebiet:
- BAU Bauingenieurwesen, Vermessungswesen; DAT Datenverarbeitung, Informatik; GEO Geowissenschaften
- Quellen der Daten:
- Experimente und Beobachtungen / experiments and observations; Abbildungen von Objekten / image of objects; Statistik und Referenzdaten / statistics and reference data
- Andere Quellen der Daten:
- Annotated point clouds
- Datentyp:
- Texte / texts; Datenbanken / data bases
- Methode der Datenerhebung:
The TUM-MLS 2016 raw point clouds (https://s.fhg.de/mls1) as the source dataset and Hitachi's Semantic Segmentation Editor (https://github.com/Hitachi-Automotive-And-Industry-Lab/semantic-segmentation-editor) for the annotation process.
- Beschreibung:
- The latest, third version of the dataset, merges 'training' and 'test' datasets into one 'pointcloud' folder, to enable more flexibility. Previously non-annotated buildings (ID...57), are now labelled. Thus, our dataset is enriched with another 16 annotated facades, which translates to extra 77 mln annotated points. The missing class in the building ID...62 has been added, too. The updated statistics presents as follows:
• 33 annotated facades and 8 non-annotated for further benchmark extension or testing
• 333 ml annotated points
• in local and global coordinate reference system
• settings file for adding your own data - Links:
The database was created on a basis of the TUM-MLS 2016 dataset: https://doi.org/10.3390/rs12111875
https://s.fhg.de/mls1To see all versions of the dataset, check out " Versions" in the bottom of the page
- Schlagworte:
- MLS point clouds; semantic segmentation, 3D reconstruction, facade reconstruction
- Technische Hinweise:
- View and download (16 GB total, 24 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1636761.003):
rsync rsync://m1636761.003@dataserv.ub.tum.de/m1636761.003/ - Sprache:
- en
- Rechte:
- by, http://creativecommons.org/licenses/by/4.0
BibTeX
Versionen
