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

Publication ,  Conference
Chen, J; Chang, Z; Qiu, Q; Li, X; Sapiro, G; Bronstein, A; Pietikäinen, M
Published in: 2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016
January 17, 2017

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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Published In

2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016

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Publication Date

January 17, 2017
 

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Chen, J., Chang, Z., Qiu, Q., Li, X., Sapiro, G., Bronstein, A., & Pietikäinen, M. (2017). RealSense = real heart rate: Illumination invariant heart rate estimation from videos. In 2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016. https://doi.org/10.1109/IPTA.2016.7820970
Chen, J., Z. Chang, Q. Qiu, X. Li, G. Sapiro, A. Bronstein, and M. Pietikäinen. “RealSense = real heart rate: Illumination invariant heart rate estimation from videos.” In 2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016, 2017. https://doi.org/10.1109/IPTA.2016.7820970.
Chen J, Chang Z, Qiu Q, Li X, Sapiro G, Bronstein A, et al. RealSense = real heart rate: Illumination invariant heart rate estimation from videos. In: 2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016. 2017.
Chen, J., et al. “RealSense = real heart rate: Illumination invariant heart rate estimation from videos.” 2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016, 2017. Scopus, doi:10.1109/IPTA.2016.7820970.
Chen J, Chang Z, Qiu Q, Li X, Sapiro G, Bronstein A, Pietikäinen M. RealSense = real heart rate: Illumination invariant heart rate estimation from videos. 2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016. 2017.

Published In

2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016

DOI

Publication Date

January 17, 2017