Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity

arXiv:2404.08184v1 Announce Type: new
Abstract: Domain shift differences between training data for deep learning models and the deployment context can result in severe performance issues for models which fail to generalize. We study the domain shift problem under the context of remote photoplethysmography (rPPG), a technique for video-based heart rate inference. We propose metrics based on model similarity which may be used as a measure of domain shift, and we demonstrate high correlation between these metrics and empirical performance. One …

abstract arxiv context cs.cv data deep learning deployment differences domain measuring performance rate shift study training training data type video