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. Through extensive evaluations and direct comparisons, we demonstrate the effectiveness of the approaches in enhancing rPPG measurements under challenging environments, contributing to the development of more reliable and effective remote vital sign monitoring technologies.
Abstract (translated)
基于视频的远程脉搏测量（rPPG）作为一种非接触式生命体征监测的有前景的技术，尤其是在受控条件下，已经得到了广泛的应用。然而，在现实世界的场景中准确测量生命体征面临着几个挑战，包括由视频编码器产生的伪影、低光噪声、失真、低动态范围、遮挡和硬件及网络限制等。在本文中，我们系统地研究了这些问题，并测量了它们对rPPG测量质量的损害。此外，我们提出了应对这些挑战的实际策略，以提高基于视频的rPPG系统的可靠性和弹性。我们详细介绍了在网络限制下进行生物信号恢复的方法，并提出了旨在保持视频帧完整性的去噪和修复技术。通过广泛的评估和直接比较，我们证明了这些方法在具有挑战性的环境中增强rPPG测量效果，为开发更可靠和有效的远程生命体征监测技术做出了贡献。
URL
https://arxiv.org/abs/2405.01230
