Body temperature estimation of a moving subject from thermographic images

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 amoving 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 degrees C.