C3I Thermal Automotive Dataset
The C3I Thermal Automotive Dataset provides > 35,000 distinct frames along with annotated thermal frames for the development of smart thermal perception system/ object detection system that will enable the automotive industry and researchers to develop safer and more efficient ADAS and self-driving car systems. The overall dataset is acquired, processed, and open-sourced in challenging weather and environmental scenarios. The dataset is recorded from a lost-cost yet effective 640x480 uncooled LWIR thermal camera. The dataset is gathered by mounting the camera stand-alone and on an electric vehicle to minimize mechanical vibrations.
This Dataset is Published by NUIG under HELIAUS EU Project.
All researchers/professionals need to follow the instructions below to access the datasets.
• If you are using this dataset it is requested to fill the google dataset dissemination form (Link: https://docs.google.com/forms/d/e/1FAIpQLSfi8K8DE4a6kBtVD3GyCXvMCcTrvSCm...). Please use institutional/ Company email address(es). Commercial emails such as Gmail are not allowed.
• Annotation for bounding boxes is provided to train YOLO/ YOLO-v5 based detectors.
• Also please cite this dataset along with the following papers.
1. M. A. Farooq, P. Corcoran, C. Rotariu and W. Shariff, "Object Detection in Thermal Spectrum for Advanced Driver-Assistance Systems (ADAS)," in IEEE Access, vol. 9, pp. 156465-156481, 2021, doi: 10.1109/ACCESS.2021.3129150.
2. M. A. Farooq, W. Shariff and P. Corcoran, "Evaluation of Thermal Imaging on Embedded GPU Platforms for Application in Vehicular Assistance Systems," in IEEE Transactions on Intelligent Vehicles, doi: 10.1109/TIV.2022.3158094.
- Thermal Frames 640x480.7z (482.66 MB)
- Video Sets.7z (263.58 MB)
- Annotated Data.7z (67.95 MB)
- data-annotation-tool.7z (6.22 MB)