Roundabout Aerial Images for Vehicle Detection

  1. De-Las-Heras, Gonzalo 1
  2. Sánchez-Soriano, Javier 2
  3. Puertas, Enrique 3
  1. 1 SICE Canada Inc.
  2. 2 Universidad Francisco de Vitoria
    info

    Universidad Francisco de Vitoria

    Pozuelo de Alarcón, España

    ROR https://ror.org/03ha64j07

  3. 3 Universidad Europea de Madrid
    info

    Universidad Europea de Madrid

    Madrid, España

    ROR https://ror.org/04dp46240

Argitaratzaile: Zenodo

Argitalpen urtea: 2022

Mota: Dataset

Laburpena

<strong>If you use this dataset, please cite this paper: <em>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 </em></strong> 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. <strong>Roundabout (scenes)</strong> <strong>Frames</strong> <strong>Car</strong> <strong>Truck</strong> <strong>Cycle</strong> <strong>Bus</strong> <strong>Empty</strong> 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 <strong>Total</strong> 15,474 236,850 2,262 4,899 1,752 552 <strong>Data augmentation</strong> x4 x4 x4 x4 x4 x4 <strong>Total</strong> 61,896 947,400 9048 19,596 7,008 2,208