Abstract
The continual measurement of the body temperature of a moving subject in a non-invasive way is a challenging task. However, doing so enables the observation of important phenomena with not much inconvenience to the subject, and can be a powerful tool for understanding physiological reactions to diseases and medications. In this paper, we present a method to obtain the body temperature on a moving subject from thermographic images. The camera’s output (a measurement for each pixel) is processed with a particle filter tracker, a clustering algorithm, and a Kalman filter to reduce tracking and measurement noise. The method was tested on videos from animal experiments and on a human patient. Tracking performance was then evaluated by comparison with manually selected regions of interest in thermographic images. The method achieves RMS temperature estimation errors of <0.1°C.
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Bilodeau, GA., Torabi, A., Lévesque, M. et al. Body temperature estimation of a moving subject from thermographic images. Machine Vision and Applications 23, 299–311 (2012). https://doi.org/10.1007/s00138-010-0313-9
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DOI: https://doi.org/10.1007/s00138-010-0313-9