WPPG Net: A Non-contact Video Based Heart Rate Extraction Network
Framework with Compatible Training Capability
- URL: http://arxiv.org/abs/2207.01697v1
- Date: Mon, 4 Jul 2022 19:52:30 GMT
- Title: WPPG Net: A Non-contact Video Based Heart Rate Extraction Network
Framework with Compatible Training Capability
- Authors: Weiyu Sun, Xinyu Zhang, Ying Chen, Yun Ge, Chunyu Ji, Xiaolin Huang
- Abstract summary: Our facial skin presents subtle color change known as remote Photoplethys (r) signal, from which we could extract the heart rate of the subject.
Recently many deep learning methods and related datasets on r signal extraction are proposed.
However, because of the time consumption blood flowing through our body and other factors, label waves such as BVP signals have uncertain delays with real r signals in some datasets.
In this paper, by analyzing the common characteristics on rhythm and periodicity of r signals and label waves, we propose a whole set of training methodology which wraps these networks so that they could remain efficient when be trained at
- Score: 21.33542693986985
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Our facial skin presents subtle color change known as remote
Photoplethysmography (rPPG) signal, from which we could extract the heart rate
of the subject. Recently many deep learning methods and related datasets on
rPPG signal extraction are proposed. However, because of the time consumption
blood flowing through our body and other factors, label waves such as BVP
signals have uncertain delays with real rPPG signals in some datasets, which
results in the difficulty on training of networks which output predicted rPPG
waves directly. In this paper, by analyzing the common characteristics on
rhythm and periodicity of rPPG signals and label waves, we propose a whole set
of training methodology which wraps these networks so that they could remain
efficient when be trained at the presence of frequent uncertain delay in
datasets and gain more precise and robust heart rate prediction results than
other delay-free rPPG extraction methods.
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