Spectral Reflectance based Heart Rate Measurement from Facial Video
Arvind Subramaniam, Rajitha K

TL;DR
This paper introduces a spectral reflectance-based method for remote heart rate measurement from facial videos that is robust to motion and illumination variations, eliminating the need for background information.
Contribution
It presents a novel illumination rectification technique and a feature point recovery system to improve HR estimation during extreme head movements.
Findings
Outperforms previous methods with a 5.21% RMS error
Robust to extreme motion and illumination changes
Does not rely on background information
Abstract
Remote detection of the cardiac pulse has a number of applications in sports and medicine, and can be used to determine the physiological state of the subject. Previous approaches to estimate Heart Rate from video require the subject to remain stationary and employ background information to eliminate illumination interferences. The present research proposes a spectral reflectance based novel illumination rectification method to eliminate illumination variations in the video. Our method does not rely on the background of the video and is robust to extreme motion interferences (head movements). Furthermore, in order to tackle extreme motion artifacts, the present framework introduces a novel feature point recovery system which recovers the feature tracking points lost during extreme head movements of the subject. Finally, the individual HR estimates from multiple feature points are…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNon-Invasive Vital Sign Monitoring · Optical Imaging and Spectroscopy Techniques · Heart Rate Variability and Autonomic Control
