What not to do in facial infrared thermographic measurements: A post data enhancement
Journal article
Pike, M., Yeboah, S. and Fu, X. (2024). What not to do in facial infrared thermographic measurements: A post data enhancement. Engineering Applications of Artificial Intelligence. 136 (Part B), p. 109027. https://doi.org/10.1016/j.engappai.2024.109027
Authors | Pike, M., Yeboah, S. and Fu, X. |
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Abstract | The accuracy of infrared thermographic measurements depends on several factors, including movement of target. In this study, accuracy of nose tip temperatures obtained in a mental workload assessment using a thermal imaging camera were impacted by participants’ movement and camera zooming/panning. To correct these measurement errors, we compared manual facial landmark identification techniques using data labelling software with an automated deep learning-based approach utilised for facial landmark tracking and evaluated both against the built-in tracking features of the thermal camera, Thermal Spot Tracking. Using the Manual Thermal Landmark Annotation measurements as the ground truth, our results show that the Automated Facial Feature Tracking approach, which is the AI based approach performed better than the Thermal Spot Tracking as it matched comparatively more spatial coordinates and temperature datapoints as well as showed comparatively lower mean relative error. The study highlights the potential of AI in enhancing the accuracy of thermographic measurements, particularly in applications involving facial temperature analysis. |
Keywords | Deep learning; Convolutional neural network; Facial landmark detection; Infrared thermography |
Year | 2024 |
Journal | Engineering Applications of Artificial Intelligence |
Journal citation | 136 (Part B), p. 109027 |
Publisher | Elsevier |
ISSN | 1873-6769 |
0952-1976 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.engappai.2024.109027 |
Web address (URL) | https://www.sciencedirect.com/science/article/pii/S0952197624011850?via%3Dihub |
Publication dates | |
Online | 23 Jul 2024 |
Publication process dates | |
Accepted | 19 Jul 2024 |
Deposited | 22 Aug 2024 |
Accepted author manuscript | License File Access Level Open |
https://openresearch.lsbu.ac.uk/item/97z64
Download files
Accepted author manuscript
EAAI-24-2757 Manuscript-3rd Revision- Clean version.docx | ||
License: CC BY 4.0 | ||
File access level: Open |
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