Towards Accurate Heart Rate Measurement from Ultra-Short Video Clips via Periodicity-Guided rPPG Estimation and Signal Reconstruction
This addresses the need for remote heart rate monitoring in scenarios with limited video duration, such as mobile health applications, though it is incremental over existing rPPG methods.
The paper tackled the problem of accurately measuring heart rate from ultra-short 2-second video clips by proposing a periodicity-guided rPPG estimation method and a signal reconstruction generator, achieving state-of-the-art performance on four benchmark datasets.
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.