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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