A visual context-awareness-based sleeping-respiration measurement system
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
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In this paper, we propose a novel tracker to capture the human breathing signal through an infrared imaging method. Human facial physiology information is used to select salient thermal features on the human face as good features to track. The major component of the tracker is Mean Shift Localization (MSL)-based particle filtering. A special measurement model is designed for particle filtering so that the tracker can handle significant head movement and object occlusion. The breathing signal is achieved based on tracking results. The experiments show that the tracker is robust and stable and the recovered breathing signal is clear enough for breathing functionality computation.