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Title:

TUM-FAÇADE

Document type:
Forschungsdaten
Publication date:
05.05.2023
Responsible:
Wysocki, Olaf
Authors:
Wysocki, Olaf ; Tan, Yue; Zhang, Jiarui ; Stilla, Uwe
Author affiliation:
TUM
Publisher:
TUM
Identifier:
doi:10.14459/2021mp1636761.003
Concept DOI:
doi:10.14459/2021mp1636761
End date of data production:
01.04.2023
Subject area:
BAU Bauingenieurwesen, Vermessungswesen; DAT Datenverarbeitung, Informatik; GEO Geowissenschaften
Resource type:
Experimente und Beobachtungen / experiments and observations; Abbildungen von Objekten / image of objects; Statistik und Referenzdaten / statistics and reference data
Other resource types:
Annotated point clouds
Data type:
Texte / texts; Datenbanken / data bases
Description:
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
Method of data assessment:

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.

Links:

The database was created on a basis of the TUM-MLS 2016 dataset: https://doi.org/10.3390/rs12111875
https://s.fhg.de/mls1

To see all versions of the dataset, check out " Versions" in the bottom of the page

Key words:
MLS point clouds; semantic segmentation, 3D reconstruction, facade reconstruction
Technical remarks:
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/
Language:
en
Rights:
by, http://creativecommons.org/licenses/by/4.0
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versions