1. Robust heart-rate estimation from facial videos using Project_ICA.
- Author
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Lin Qi, Huidong Yu, Lisheng Xu, Ramadhani Selemani Mpanda, and Stephen E Greenwald
- Subjects
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PLETHYSMOGRAPHY , *ACTIVE recovery , *HEART beat , *VIDEOS , *HUMAN facial recognition software , *MOTION analysis , *PHOTOPLETHYSMOGRAPHY - Abstract
Objective: Remote photoplethysmography (rPPG) can achieve non-contact measurement of heart rate (HR) from a continuous video sequence by scanning the skin surface. However, practical applications are still limited by factors such as non-rigid facial motion and head movement. In this work, a detailed system framework for remotely estimating heart rate from facial videos under various movement conditions is described. Approach: After the rPPG signal has been obtained from a defined region of the facial skin, a method, termed ‘Project_ICA’, based on a skin reflection model, is employed to extract the pulse signal from the original signal. Main results: To evaluate the performance of the proposed algorithm, a dataset containing 112 videos including the challenges of various skin tones, body motion and HR recovery after exercise was created from 28 participants. Significance: The results show that Project_ICA, when evaluated by several criteria, provides a more accurate and robust estimate of HR than most existing methods, although problems remain in obtaining reliable measurements from dark-skinned subjects. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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