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Title:

C.DOT Ground Truth Dataset

Document type:
Forschungsdaten
Publication date:
28.06.2021
Responsible:
Thiel, Kevin Kennard
Authors:
Thiel, Kevin Kennard
Author affiliation:
TUM
Publisher:
TUM
Identifier:
doi:10.14459/2021mp1614575.001
Concept DOI:
doi:10.14459/2021mp1614575
End date of data production:
04.12.2020
Subject area:
DAT Datenverarbeitung, Informatik; VER Technik der Verkehrsmittel
Other subject areas:
Object Tracking ; Industry 4.0 ; Ground Truth ; Augmented Reality, Computer Vision, Artificial Intelligence
Resource type:
Abbildungen von Objekten / image of objects; Statistik und Referenzdaten / statistics and reference data
Data type:
Bilder / images; mehrdimensionale Visualisierungen oder Modelle / models; Texte / texts; Datenbanken / data bases
Other data type:
Camera Calibration File
Description:
A dataset for validation of 6-dof model trackers. It includes image sets, camera calibration data, ground truth data and projection data for each image. This data is provided for four different objects. For each object 3D model data is provided too. Two of those objects are taken from automotive engineering use cases of the Volkswagen Group. While the other two models are 3D printed versions of popular computer graphics models of the Stanford University Computer Graphics Laboratory. The data...     »
Method of data assessment:
The data was created for research of object tracking for superimposed augmented reality in the context of automotive engineering. The images were taken using a calibrated webcam. The ground truth was captured using an accurate model-based tracker. The specific reason for capturing the data was to evaluate machine-learning based object trackers trained on synthetic data only. More information can be found in the provided readme.txt file.
Links:

The corresponding journal article can be found under the following doi: 10.1109/TVCG.2021.3089096

https://www.in.tum.de/far/mitarbeiter/kevin-thiel/
http://graphics.stanford.edu/data/3Dscanrep/
https://www.volkswagen.de/

Key words:
Image; Images; Image Sets; Camera Calibration; Ground Truth; Model; Models; Objects; Tracking; Object Tracking; Model-based Tracking; 6-dof Tracking; 6-dof, Six Degrees of Freedom; Automotive; Augmented Reality; Projection; Reference; Reference Points
Technical remarks:
View and download (1.41 GB, 2 files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1614575):
rsync rsync://m1614575.001@dataserv.ub.tum.de/m1614575.001/
Language:
en
Rights:
by, http://creativecommons.org/licenses/by/4.0
Other rights:
Exception: For the reuse of the 3D printed versions of popular computer graphics models of the Stanford University Computer Graphics Laboratory, please consider the conditions of reuse of the repository (http://graphics.stanford.edu/data/3Dscanrep/). When using the data you agree to acknowledge the following related publication: “K. K. Thiel, F. Naumann, E. Jundt, S. Guennemann and G. J. Klinker, C.DOT - Convolutional Deep Object Tracker for Augmented Reality Based Purely on Synthetic Data, in I...     »
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