Heart Rate Estimation from Face Videos Against Motion Interference

YANG Zhao; YANG Xuezhi; HUO Liang; LIU Xuenan; LI Jiangshan

doi:10.11999/JEIT170824

Volume 40 Issue 6

May 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(6): 1345-1352

YANG Zhao, YANG Xuezhi, HUO Liang, LIU Xuenan, LI Jiangshan. Heart Rate Estimation from Face Videos Against Motion Interference[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1345-1352. doi: 10.11999/JEIT170824

Citation:

YANG Zhao, YANG Xuezhi, HUO Liang, LIU Xuenan, LI Jiangshan. Heart Rate Estimation from Face Videos Against Motion Interference[J]. Journal of Electronics & Information Technology, 2018, 40(6): 1345-1352. doi: 10.11999/JEIT170824

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Heart Rate Estimation from Face Videos Against Motion Interference

doi: 10.11999/JEIT170824

Funds:

Training Programme Foundation for Application of Scientific and Technological Achievements of Hefei University of Technology (JZ2016YYPY0051)

Received Date: 2017-08-23
Rev Recd Date: 2018-02-01
Publish Date: 2018-06-19

Abstract

Abstract

A novel non-contact heart rate estimation method is proposed to deal with the issue of heart rate measurement from face videos under motion interference in realistic situations, it is hard to estimate heart rate accurately using existing methods. Firstly, the discriminative response map fitting method and KLT tracking algorithm are used to eliminate the influence of face rigid motion. Then the chrominance features are selected to estimate heart rate with two steps because of the robustness to facial movements. The frequency and spatial domain weights are assigned through spatial gradient to eliminate the influence of non-rigid motion. Finally, the accurate average heart rate value and pulse wave signal waveform can be acquired from different face regions. Compared with three other methods, experimental results indicate that the proposed method enhances the consistency of estimated waveform and ground truth waveform and has obvious superiority in accuracy and robustness of heart rate estimation.
- Face video detection,
- Two-step heart rate estimation,
- PhotoPlethysmoGraphy (PPG),
- Discriminative Response Map Fitting (DRMF),
- Chrominance features,
- Spatial gradient

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References(18)

References

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