2025/06/27 by Pei-Kai Huang, Pei-Kai Huanga, Huanga, Pei-Kai +13
Computer Science · Engineering · Medicine · #Heart Rate Variability and Autonomic Control #Non-Invasive Vital Sign Monitoring #Optical Imaging and Spectroscopy Techniques #cs.CV
paper · pdf · doi:10.48550/arxiv.2506.22078
openalex publication_date 2025/06/27 · openalex created_date 2025/10/10 · arxiv created 2026/07/31 · openalex updated_date 2026/07/31 · arxiv updated 2026/08/03
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.