The First Vision For Vitals (V4V) Challenge for Non-Contact Video-Based Physiological Estimation

TL;DR

This paper introduces the V4V Challenge, a benchmark for evaluating non-contact video-based physiological estimation methods in naturalistic conditions, providing a standardized dataset and evaluation protocol.

Contribution

It presents the first comprehensive benchmark dataset and evaluation framework for remote PPG methods under realistic, uncontrolled conditions.

Findings

Baseline methods evaluated on the dataset

Insights into challenges of naturalistic video-based physiological estimation

Guidelines for future research in remote vital signs measurement

Abstract

Telehealth has the potential to offset the high demand for help during public health emergencies, such as the COVID-19 pandemic. Remote Photoplethysmography (rPPG) - the problem of non-invasively estimating blood volume variations in the microvascular tissue from video - would be well suited for these situations. Over the past few years a number of research groups have made rapid advances in remote PPG methods for estimating heart rate from digital video and obtained impressive results. How these various methods compare in naturalistic conditions, where spontaneous behavior, facial expressions, and illumination changes are present, is relatively unknown. To enable comparisons among alternative methods, the 1st Vision for Vitals Challenge (V4V) presented a novel dataset containing high-resolution videos time-locked with varied physiological signals from a diverse population. In this paper, we outline the evaluation protocol, the data used, and the results. V4V is to be held in conjunction with the 2021 International Conference on Computer Vision.