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Dayton Annotated Laser Earth Scan (DALES)

A Large-scale Aerial LiDAR Data Set for Point Cloud Segmentation

DALES

Summary

We present the Dayton Annotated Laser Earth Scan (DALES) data set, a new large-scale aerial LiDAR data set with nearly a half-billion points spanning 10 square kilometers of area. DALES contains forty scenes of dense, labeled aerial data spanning multiple scene types, including urban, suburban, rural, and commercial. The data was hand-labeled by a team of expert LiDAR technicians into eight categories: ground, vegetation, cars, trucks, poles, power lines, fences, and buildings. We present the entire data set, split into testing and training, and provided in 3 different data formats. The goal of this data set is to help advance the field of deep learning within aerial LiDAR.

There are two sets of data covering the same geographical area:

  • DALES: the original dataset containing semantic segmentation labels.
  • DALES Objects: the second version containing semantic labels, instance labels, and intensity data.

Image


Papers

You can find a detailed description of DALES in our paper.  If you use the DALES data provided, please cite the following:

@inproceedings{varney2020dales,
  title={DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentation},
  author={Varney, Nina and Asari, Vijayan K and Graehling, Quinn},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  pages={186--187},
  year={2020}
}

You can find the data description for DALES Objects in our paper. If you use the DALES Objects data provided, please cite the following:

@article{9469802,
author={Singer, Nina M. and Asari, Vijayan K.},
journal={IEEE Access},
title={DALES Objects: A Large Scale Benchmark Dataset for Instance Segmentation in Aerial Lidar},
year={2021},
volume={},
number={},
pages={1-1},
doi={10.1109/ACCESS.2021.3094127}}

Download

The data set is pre-split into 29 training files and 11 testing files, with the following categories: ground(1), vegetation(2), cars(3), trucks(4), power lines(5), fences(6), poles(7) and buildings(8).


The data is available for download here.


Acknowledgments

The data set presented in this paper contains information licensed under the Open Government License – City of Surrey.

We would like to thank the City of Surrey for generously providing the raw data presented in this paper. For more information about the raw data and other data sources like it please see their Open Data Site.


Copyright

The annotated data set presented on this site is licensed under Creative Commons 3.0. This data may not be used for commercial purposes. If you use, adapt, or build upon this data set remember to cite our paper.

We will consider commercial usage on a case-by-case basis. Please contact us for more information.


Contact

If you used our DALES data set we would love to hear from you! Please consider sending us a message about your results and any feedback you have.

For additional questions about this data set or inquiries about commercial use, please contact nsinger1@udayton.edu.

 

dales

CONTACT

Vision Lab, Dr. Vijayan Asari, Director

Kettering Lab
300 College Park
Dayton, Ohio 45469 - 0232
937-229-1779
Email
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