Exploring Thermography Technology: A Comprehensive Facial Dataset for Face Detection, Recognition, and Emotion
<|reference_start|>Exploring Thermography Technology: A Comprehensive Facial Dataset for Face Detection, Recognition, and Emotion: This dataset includes 6823 thermal images captured using a UNI-T UTi165A camera for face detection, recognition, and emotion analysis. It consists of 2485 facial recognition images depicting emotions (happy, sad, angry, natural, surprised), 2054 images for face recognition, and 2284 images for face detection. The dataset covers various conditions, color palettes, shooting angles, and zoom levels, with a temperature range of -10{\deg}C to 400{\deg}C and a resolution of 19,200 pixels. It serves as a valuable resource for advancing thermal imaging technology, aiding in algorithm development, and benchmarking for facial recognition across different palettes. Additionally, it contributes to facial motion recognition, fostering interdisciplinary collaboration in computer vision, psychology, and neuroscience. The dataset promotes transparency in thermal face detection and recognition research, with applications in security, healthcare, and human-computer interaction.<|reference_end|>
@article{abuhussein2024exploring,
    title={Exploring Thermography Technology: A Comprehensive Facial Dataset for
  Face Detection, Recognition, and Emotion},
    author={Mohamed Fawzi Abdelshafie Abuhussein, Ashraf Darwish and Aboul Ella
  Hassanien},
    journal={arXiv preprint arXiv:2407.09494},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.09494},
    primaryClass={cs.CV cs.HC}
}