Evaluation of Video-Based rPPG in Challenging Environments: Artifact Mitigation and Network Resilience
Nhi Nguyen, Le Nguyen, Honghan Li, Miguel Bordallo L\'opez,, Constantino \'Alvarez Casado

TL;DR
This paper investigates the challenges faced by video-based remote photoplethysmography (rPPG) in real-world environments and proposes strategies to mitigate artifacts, noise, and network issues to improve measurement reliability.
Contribution
It systematically analyzes the effects of artifacts and network constraints on rPPG and introduces practical mitigation techniques for enhanced system resilience.
Findings
Proposed denoising and inpainting methods improve signal quality.
Mitigation strategies increase rPPG accuracy in challenging conditions.
Enhanced robustness of remote vital sign monitoring systems.
Abstract
Video-based remote photoplethysmography (rPPG) has emerged as a promising technology for non-contact vital sign monitoring, especially under controlled conditions. However, the accurate measurement of vital signs in real-world scenarios faces several challenges, including artifacts induced by videocodecs, low-light noise, degradation, low dynamic range, occlusions, and hardware and network constraints. In this article, we systematically investigate comprehensive investigate these issues, measuring their detrimental effects on the quality of rPPG measurements. Additionally, we propose practical strategies for mitigating these challenges to improve the dependability and resilience of video-based rPPG systems. We detail methods for effective biosignal recovery in the presence of network limitations and present denoising and inpainting techniques aimed at preserving video frame integrity.…
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
TopicsImage and Video Quality Assessment · Software-Defined Networks and 5G · Physical Unclonable Functions (PUFs) and Hardware Security
MethodsInpainting
