Respiratory rate estimation via simultaneously tracking and segmentation

A novel strategy of simultaneously tracking and segmentation is proposed for human respiratory rate estimation from thermal infrared, which can be applicable to contact-free polygraphy, airport health screening and patient monitoring system. In this framework, by carefully selecting the adaptive observation model for the tracking template and taking the intensity variation pattern of breathing into account, we developed a tracker which is not only to track successfully the region of interest (ROI) which is subject to both physiological and abrupt motion change, but also to segment out the breathing flow region simultaneously, without increasing any large extra computation. The experimental result demonstrated both its stability in tracking and accuracy improvement in recovery of the temperature profile on breathing, compared with other trackers without involvement of segmentation. Besides estimating respiratory rate, the proposed algorithm can be also utilized for any applications regarding the automatic detection and tracking of pixels experiencing periodic intensity variation.