Remote Heart Rate Measurement from RGB-NIR Video
Based on Spatial and Spectral Face Patch Selection


Shiika Kado, Yusuke Monno, Kenta Moriwaki, Kazunori Yoshizaki, Masayuki Tanaka, Masatoshi Okutomi
International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2018

Proposed Algorithm Overview

Overview

Abstract

In this paper, we propose a novel heart rate (HR) estimation method using simultaneously recorded RGB and near-infrared (NIR) face videos. The key idea of our method is to automatically select suitable face patches for HR estimation in both spatial and spectral domains. The spatial and spectral face patch selection enables us to robustly estimate HR under various situations, including scenes under which existing RGB camera-based methods fail to accurately estimate HR. For a challenging scene in low light and with light fluctuations, our method can successfully estimate HR for all 20 subjects (±3 beats per minute), while the RGB camera-based methods succeed only for 25% of the subjects.

Publications

  • Remote Heart Rate Measurement from RGB-NIR Video Based on Spatial and Spectral Face Patch Selection [PDF] [Slide]
    Shiika Kado, Yusuke Monno, Kenta Moriwaki, Kazunori Yoshizaki, Masayuki Tanaka, Masatoshi Okutomi
    International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC2018), pp.5676-5680, July, 2018.
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