Computer Science > Computer Vision and Pattern Recognition
arXiv:2309.06095 (cs)
[Submitted on 12 Sep 2023]
Title:Estimating exercise-induced fatigue from thermal facial images
View a PDF of the paper titled Estimating exercise-induced fatigue from thermal facial images, by Manuel Lage Ca\~nellas and 3 other authors
View PDFAbstract:Exercise-induced fatigue resulting from physical activity can be an early indicator of overtraining, illness, or other health issues. In this article, we present an automated method for estimating exercise-induced fatigue levels through the use of thermal imaging and facial analysis techniques utilizing deep learning models. Leveraging a novel dataset comprising over 400,000 thermal facial images of rested and fatigued users, our results suggest that exercise-induced fatigue levels could be predicted with only one static thermal frame with an average error smaller than 15\%. The results emphasize the viability of using thermal imaging in conjunction with deep learning for reliable exercise-induced fatigue estimation.
| Comments: | 5 pages |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2309.06095 [cs.CV] |
| (orarXiv:2309.06095v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2309.06095 arXiv-issued DOI via DataCite |
Submission history
From: Miguel Bordallo Lopez [view email][v1] Tue, 12 Sep 2023 10:00:23 UTC (2,926 KB)
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View a PDF of the paper titled Estimating exercise-induced fatigue from thermal facial images, by Manuel Lage Ca\~nellas and 3 other authors
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