2秒视频测心率，靠周期性引导和信号重建提升精度
Ultra-Short rPPG Estimation via Periodicity Guidance and Signal Reconstruction
- 用长视频真值引导短视频周期性，增强信号一致性
- 通过生成器重建长信号，减少频谱泄漏导致的误差
- 在4个数据集上达到当前最佳效果，适合快速心率监测
许多远程心率测量方法专注于约10秒视频片段的心率估计，却忽略了超短视频（如2秒）的需求。本文针对从2秒视频中准确测量心率的挑战，提出两项关键技术：首先，为克服超短视频中心跳周期数过少的问题，设计了一种周期性引导的rPPG估计方法，强制使短时估计信号与更长的真值信号保持一致周期性；其次，为缓解频谱泄漏引起的估计偏差，引入生成器从短信号重建更长的rPPG信号，同时保持周期一致性，从而实现更精准的心率测量。在四个rPPG基准数据集上的大量实验表明，所提方法不仅能有效实现2秒视频的心率估计，且性能优于现有技术，达到当前最优水平。
原文摘要 · Abstract (English)
Many remote Heart Rate (HR) measurement methods focus on estimating remote photoplethysmography (rPPG) signals from video clips lasting around 10 seconds but often overlook the need for HR estimation from ultra-short video clips. In this paper, we aim to accurately measure HR from ultra-short 2-second video clips by specifically addressing two key challenges. First, to overcome the limited number of heartbeat cycles in ultra-short video clips, we propose an effective periodicity-guided rPPG estimation method that enforces consistent periodicity between rPPG signals estimated from ultra-short clips and their much longer ground truth signals. Next, to mitigate estimation inaccuracies due to spectral leakage, we propose including a generator to reconstruct longer rPPG signals from ultra-short ones while preserving their periodic consistency to enable more accurate HR measurement. Extensive experiments on four rPPG estimation benchmark datasets demonstrate that our proposed method not only accurately measures HR from ultra-short video clips but also outperform previous rPPG estimation techniques to achieve state-of-the-art performance.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。