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Non-contact image photoplethysmography has gained a lot of attention during the last 5 years. Starting with the work of Verkruysse et al. 1, various methods for estimation of the human pulse rate from video sequences of the face under ambient illumination have been presented. Applied on a mobile service robot aimed to motivate elderly users for physical exercises, the pulse rate can be a valuable information in order to adapt to the users conditions. For this paper, a typical processing pipeline was implemented on a mobile robot, and a detailed comparison of methods for face segmentation was conducted, which is the key factor for robust pulse rate extraction even, if the subject is moving. A benchmark data set is introduced focusing on the amount of motion of the head during the measurement.
Stricker et al. (Fri,) studied this question.