Published March 16, 2022 | Version 1.0.1
Dataset Open

Roundabout Aerial Images for Vehicle Detection

  • 1. SICE Canada Inc.
  • 2. Universidad Francisco de Vitoria
  • 3. Universidad Europea de Madrid

Description

If you use this dataset, please cite this paper: Puertas, E.; De-Las-Heras, G.; Fernández-Andrés, J.; Sánchez-Soriano, J. Dataset: Roundabout Aerial Images for Vehicle Detection. Data 2022, 7, 47. https://doi.org/10.3390/data7040047

This publication presents a dataset of Spanish roundabouts aerial images taken from an UAV, along with annotations in PASCAL VOC XML files that indicate the position of vehicles within them. Additionally, a CSV file is attached containing information related to the location and characteristics of the captured roundabouts. This work details the process followed to obtain them: image capture, processing and labeling. The dataset consists of 985,260 total instances: 947,400 cars, 19,596 cycles, 2,262 trucks, 7,008 buses and 2,208 empty roundabouts, in 61,896 1920x1080px JPG images. These are divided into 15,474 extracted images from 8 roundabouts with different traffic flows and 46,422 images created using data augmentation techniques. The purpose of this dataset is to help research on computer vision on the road, as such labeled images are not abundant. It can be used to train supervised learning models, such as convolutional neural networks, which are very popular in object detection.

 

Roundabout (scenes)

Frames

Car

Truck

Cycle

Bus

Empty

1 (00001)

1,996

34,558

0

4229

0

0

2 (00002)

514

743

0

0

0

157

3 (00003-00017)

1,795

4822

58

0

0

0

4 (00018-00033)

1,027

6615

0

0

0

0

5 (00034-00049)

1,261

2248

0

550

0

81

6 (00050-00052)

5,501

180,342

1420

120

1376

0

7 (00053)

2,036

5,789

562

0

226

92

8 (00054)

1,344

1,733

222

0

150

222

Total

15,474

236,850

2,262

4,899

1,752

552

Data augmentation

x4

x4

x4

x4

x4

x4

Total

61,896

947,400

9048

19,596

7,008

2,208

Notes

Funding: This publication is part of the I+D+i projects with reference PID2019-104793RB-C32, PIDC2021-121517-C33, funded by MCIN/AEI/10.13039/501100011033/, S2018/EMT-4362/"SEGVAUTO4.0-CM" funded by Regional Government of Madrid and "ESF and ERDF A way of making Europe".

Files

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