Delft Windmill Interior and Exterior Laser Scanning Point Clouds
Datacite citation style:
Beril Sirmacek (2015): Delft Windmill Interior and Exterior Laser Scanning Point Clouds. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:daea472d-2ca5-4765-9f1b-bd3200de4b41
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
Data set for the Urban Data Modelling and Visualisation (UDMV 2015) Contest: {https://3d.bk.tudelft.nl/events/udmv2015/contest.html}.
The objective of this contest is to give opportunity to researchers to evaluate and share methods that they have developed for 3D modelling of complex urban structures.
The dataset ‘Delft Windmill Interior and Exterior Laser Scanning Point Clouds’ consists of a recent terrestrial LiDAR acquisition of a historical windmill in Delft (exterior and interior). Researchers are invited to develop the best use of this dataset, showcasing their work and interest. For instance, an idea would be to generate a full 3D model of the historical windmill using its exterior and interior laser scanning point clouds, or to develop a nice visualisation.
Contributing to the contest is open to researchers with expertise from various disciplines, such as but not limited to computer vision, remote sensing, 3D modelling, and visualisation.
The UDMV 2015 Contest is organised as a part of the 3rd Eurographics Workshop on Urban Data Modelling and Visualisation (UDMV), which will be held in Delft (Netherlands) in November 2015. The contest dataset is provided by TU Delft Library as an open public data set. The participation in this contest is FREE, and it does not entail a participation at the workshop (albeit it is encouraged).
Contributors: 3-D Geoinformation Research Group, Adriaan van Natijne, Ben Gorte, Eva Stierman, Filip Biljecki, Jeroen Lichtenauer, Jinhu Wang, Joppe Roebroeks, Roderik Lindenbergh
history
- 2015-06-30 first online, published, posted
publisher
Delft University of Technology
format
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references
organizations
TU Delft, Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote Sensing
DATA
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