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Authors: Vijul Shah 1 ; Brian B. Moser 1 ; 2 ; Ko Watanabe 1 ; 2 and Andreas Dengel 2 ; 1

Affiliations: 1 RPTU Kaiserslautern-Landau, Germany ; 2 German Research Center for Artificial Intelligence (DFKI), Germany

Keyword(s): Pupil Diameter Prediction, Image Super-Resolution.

Abstract: Capturing pupil diameter is essential for assessing psychological and physiological states such as stress levels and cognitive load. However, the low resolution of images in eye datasets often hampers precise measurement. This study evaluates the impact of various upscaling methods, ranging from bicubic interpolation to advanced super-resolution, on pupil diameter predictions. We compare several pre-trained methods, including CodeFormer, GFPGAN, Real-ESRGAN, HAT, and SRResNet. Our findings suggest that pupil diameter prediction models trained on upscaled datasets are highly sensitive to the selected upscaling method and scale. Our results demonstrate that upscaling methods consistently enhance the accuracy of pupil diameter prediction models, highlighting the importance of upscaling in pupilometry. Overall, our work provides valuable insights for selecting upscaling techniques, paving the way for more accurate assessments in psychological and physiological research.

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Paper citation in several formats:
Shah, V., Moser, B. B., Watanabe, K. and Dengel, A. (2025). Webcam-Based Pupil Diameter Prediction Benefits from Upscaling. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-737-5; ISSN 2184-433X, SciTePress, pages 376-385. DOI: 10.5220/0013162800003890

@conference{icaart25,
author={Vijul Shah and Brian B. Moser and Ko Watanabe and Andreas Dengel},
title={Webcam-Based Pupil Diameter Prediction Benefits from Upscaling},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2025},
pages={376-385},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013162800003890},
isbn={978-989-758-737-5},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Webcam-Based Pupil Diameter Prediction Benefits from Upscaling
SN - 978-989-758-737-5
IS - 2184-433X
AU - Shah, V.
AU - Moser, B.
AU - Watanabe, K.
AU - Dengel, A.
PY - 2025
SP - 376
EP - 385
DO - 10.5220/0013162800003890
PB - SciTePress

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