Real-time facial feature tracking in poor quality thermal imagery

Recently, facial feature tracking systems have become more and more popular because of many possible use cases. Especially in medical applications location of the face and facial features are very useful. Many researches have presented methods to detect and track facial features in visible light. However, facial feature analysis in thermography may also be very advantageous. Some examples of using infrared imagery in medicine include the estimation of the respiration rate using an analysis of temperature changes in the area below nose region. Moreover, due to technological development small thermal cameras may be embedded into wearable devices, like smart glasses and used to support remote patient monitoring. Therefore, in this paper, we focused on face tracking in low quality thermal images. Especially, we compared four interest points detectors for facial feature tracking in thermal images. All methods were tested for processing time, displacement of detected areas and errors of calculated mean value of pixel intensities in the detected nose region. Finally, we presented a fully automatic system for facial features tracking, which allows to process one frame in about 27.7ms (Harris), 23.9ms (ORB), 19.7ms (SIFT), 27.6ms (SURF) with acceptable accuracy (Harris - 7.2±4.3%, ORB 9.9±2.2%, SIFT 7.0±1.9%, SURF 8.9±2.7%).