@misc{mcduff2020advancing,
author = {McDuff, Daniel and Hernandez, Javier and Wood, Erroll and Liu, Xin and Baltrusaitis, Tadas},
title = {Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars},
howpublished = {ArXiv},
year = {2020},
month = {October},
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.},
url = {http://approjects.co.za/?big=en-us/research/publication/advancing-non-contact-vital-sign-measurement-using-synthetic-avatars/},
}