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Ultra-short rPPG estimation via periodicity guidance and signal reconstruction
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Ultra-short rPPG estimation via periodicity guidance and signal reconstruction

Pei-Kai Huang, Ya-Ting Chan, Kuan-Wen Chen, Chiou-Ting Hsu, Xiaoding Wang 和 Md. Jalil Piran
Pattern recognition, 卷.180, 頁.114573
12/2026
Web of Science ID: WOS:001843583400001

摘要

Heart rate measurement rPPG estimation Signal reconstruction Spectral leakage Ultra-short video rPPG estimation
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 outperforms previous rPPG estimation techniques to achieve state-of-the-art performance. •We propose a periodicity-guided framework for ultra-short rPPG estimation.•A periodicity consistency constraint addresses insufficient heartbeat cycles.•Signal reconstruction mitigates spectral leakage for accurate HR estimation.•Extensive experiments demonstrate superior performance over existing methods.

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