University of Oulu

J. Chen et al., "RealSense = real heart rate: Illumination invariant heart rate estimation from videos," 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA), Oulu, 2016, pp. 1-6. doi: 10.1109/IPTA.2016.7820970

RealSense = real heart rate : illumination invariant heart rate estimation from videos

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Author: Chen, Jie1; Chang, Zhuoqing2; Qiu, Qiang2;
Organizations: 1University of Oulu, Finland
2Duke University, USA
3Tel Aviv University, Israel
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.7 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2016
Publish Date: 2020-01-14


Recent studies validated the feasibility of estimating heart rate from human faces in RGB video. However, test subjects are often recorded under controlled conditions, as illumination variations significantly affect the RGB-based heart rate estimation accuracy. Intel newly-announced low-cost RealSense 3D (RGBD) camera is becoming ubiquitous in laptops and mobile devices starting this year, opening the door to new and more robust computer vision. RealSense cameras produce RGB images with extra depth information inferred from a latent near-infrared (NIR) channel. In this paper, we experimentally demonstrate, for the first time, that heart rate can be reliably estimated from RealSense near-infrared images. This enables illumination invariant heart rate estimation, extending the heart rate from video feasibility to low-light applications, such as night driving. With the (coming) ubiquitous presence of RealSense devices, the proposed method not only utilizes its near-infrared channel, designed originally to be hidden from consumers; but also exploits the associated depth information for improved robustness to head pose.

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ISBN: 978-1-4673-8910-5
ISBN Print: 978-1-4673-8911-2
Pages: 1 - 6
DOI: 10.1109/IPTA.2016.7820970
Host publication: 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA), 12 - 15 Dec 2016 Oulu, Finland
Host publication editor: Bordallo López, Miguel
Hadid, Abdenour
Pietikäinen, Matti
Conference: International Conference on Image Processing Theory, Tools and Applications
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Funding: This work was sponsored by the Academy of Finland, Infotech Oulu and partially supported by ONR, ARO, NSF and NGA.
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