Remote photo-plethysmography (rPPG) uses a camera to estimate a person's heart rate (HR). Similar to how heart rate can provide useful information about a person's vital signs, insights about the underlying physio/psychological conditions can be obtained from heart rate variability (HRV). HRV is a measure of the fine fluctuations in the intervals between heart beats. However, this measure requires temporally locating heart beats with a high degree of precision. We introduce a refined and efficient real-time rPPG pipeline with novel filtering and motion suppression that not only estimates heart rates, but also extracts the pulse waveform to time heart beats and measure heart rate variability. This unsupervised method requires no rPPG specific training and is able to operate in real-time. We also introduce a new multi-modal video dataset, VicarPPG 2, specifically designed to evaluate rPPG algorithms on HR and HRV estimation. We validate and study our method under various conditions on a comprehensive range of public and self-recorded datasets, showing state-of-the-art results and providing useful insights into some unique aspects. Lastly, we make available CleanerPPG, a collection of human-verified ground truth peak/heart-beat annotations for existing rPPG datasets. These verified annotations should make future evaluations and benchmarking of rPPG algorithms more accurate, standardized and fair.
翻译：远距离光膜照相仪(rPPG)使用相机来估计一个人的心跳率(HR)。类似心脏率如何能提供关于一个人生命迹象的有用信息,可以从心率变异中获得对基本生理/心理条件的洞察力(HRV)。HRV是心脏跳动间隔细微波动的量度。然而,这一措施要求用高度精确的方式对心脏跳动进行时间定位。我们引入一个精细高效的实时RPPG管道,配有新型过滤和运动抑制,不仅估计心跳率,还提取脉冲波形,以测量心脏跳动和测量心率变异性。这种不受监督的方法不需要 RPPG的具体培训,而且能够实时运作。我们还引入一个新的多模式视频数据集,VicarPG 2, 专门用来评估 RPG 和HRV 估计的算法。我们在各种条件下验证和研究我们的方法,在一系列全面的公开和自我记录的数据集中,显示状态结果,并提供更精确的脉动脉冲分析。最后,我们为G的更精确的直观/最新图表收集了一些独特的基础。最后,我们提供了更精确的、更精确的图表。
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