This paper presents a method to track an animal in low-contrast thermographic images in order to obtain its body temperature. This work was done in the context of the study of atypical febrile seizures. To solve this tracking problem, we propose a method based on morphological operations on the area to track using regions resulting from consecutive frame differences. A Gaussian model is then used to classify tracked area pixels into animal and background pixels to further remove outliers. The temperature of the animal is taken as the mean of the tracked area. Experimental results show that we obtain, in general, temperature estimation within 1°C from ground-truth for videos as long as 16000 frames.
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