An urban traffic dataset composed of visible images and their semantic segmentation generated by the CARLA simulator

  1. Sergio Bemposta Rosende 1
  2. Javier, Sánchez-Soriano 2
  3. David San José Gavilán 1
  1. 1 Universidad Europea
  2. 2 Universidad Francisco de Vitoria
    info

    Universidad Francisco de Vitoria

    Pozuelo de Alarcón, España

    ROR https://ror.org/03ha64j07

Éditeur: Zenodo

Année de publication: 2023

Type: Dataset

CC BY 4.0

DOI: 10.5281/ZENODO.10058944 lock_openAccès ouvert editor

Résumé

If you use this dataset please cite this paper: Rosende, S.B.; Gavilán, D.S.J.; Fernández-Andrés, J.; Sánchez-Soriano, J. An Urban Traffic Dataset Composed of Visible Images and Their Semantic Segmentation Generated by the CARLA Simulator. Data 2024, 9, 4. https://doi.org/10.3390/data9010004 A dataset of aerial urban traffic images and their semantic segmentation is presented to be used to train computer vision algorithms, among which those based on convolutional neural networks stand out. The images have been generated using the CARLA simulator (but would be like those that could be obtained with fixed aerial cameras or by using AUVs) in the field of intelligent transportation management. The presented dataset is available and accessible to improve the performance of vision and road traffic management systems, especially for the detection of incorrect or dangerous maneuvers.