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arXiv · 2010.12949

Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars

Daniel McDuff·Javier Hernandez·Erroll Wood·Xin Liu·Tadas Baltrusaitis
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Abstract

Non-contact physiological measurement has the potential to provide low-cost, non-invasive health monitoring. However, machine vision approaches are often limited by the availability and diversity of annotated video datasets resulting in poor generalization to complex real-life conditions. To address these challenges, this work proposes the use of synthetic avatars that display facial blood flow changes and allow for systematic generation of samples under a wide variety of conditions. Our results show that training on both simulated and real video data can lead to performance gains under challenging conditions. We show state-of-the-art performance on three large benchmark datasets and improved robustness to skin type and motion.

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Daniel McDuff, Javier Hernandez, Erroll Wood, Xin Liu, Tadas Baltrusaitis. 2020-10-24. Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars. https://arxiv.org/abs/2010.12949

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