Recent studies in computer vision have shown that, while practically invisible to a human observer, skin color changes due to blood flow can be captured on face videos and, surprisingly, be used to estimate the heart rate (HR). While considerable progress has been made in the last few years, still many issues remain open. In particular, stateof-the-art approaches are not robust enough to operate in natural conditions (e.g. in case of spontaneous movements, facial expressions, or illumination changes). Opposite to previous approaches that estimate the HR by processing all the skin pixels inside a fixed region of interest, we introduce a strategy to dynamically select face regions useful for robust HR estimation. Our approach, inspired by recent advances on matrix completion theory, allows us to predict the HR while simultaneously discover the best regions of the face to be used for estimation. Thorough experimental evaluation conducted on public benchmarks suggests that the proposed approach significantly outperforms state-ofthe-art HR estimation methods in naturalistic conditions.

Self-adaptive matrix completion for heart rate estimation from face videos under realistic conditions / Tulyakov, Sergey; Alameda Pineda, Xavier; Ricci, E.; Yin, L.; Cohn, J. F.; Sebe, Niculae. - (2016), pp. 2396-2404. (Intervento presentato al convegno CVPR 2016 tenutosi a Las Vegas nel 26 June-1 July 2016) [10.1109/CVPR.2016.263].

Self-adaptive matrix completion for heart rate estimation from face videos under realistic conditions

Tulyakov, Sergey;Alameda Pineda, Xavier;Ricci, E.;Sebe, Niculae
2016-01-01

Abstract

Recent studies in computer vision have shown that, while practically invisible to a human observer, skin color changes due to blood flow can be captured on face videos and, surprisingly, be used to estimate the heart rate (HR). While considerable progress has been made in the last few years, still many issues remain open. In particular, stateof-the-art approaches are not robust enough to operate in natural conditions (e.g. in case of spontaneous movements, facial expressions, or illumination changes). Opposite to previous approaches that estimate the HR by processing all the skin pixels inside a fixed region of interest, we introduce a strategy to dynamically select face regions useful for robust HR estimation. Our approach, inspired by recent advances on matrix completion theory, allows us to predict the HR while simultaneously discover the best regions of the face to be used for estimation. Thorough experimental evaluation conducted on public benchmarks suggests that the proposed approach significantly outperforms state-ofthe-art HR estimation methods in naturalistic conditions.
2016
Proceedings 29th IEEE Conference on Computer Vision and Pattern Recognition
Los Alamitos, CA
IEEE Computer Society
978-1-4673-8850-4
Tulyakov, Sergey; Alameda Pineda, Xavier; Ricci, E.; Yin, L.; Cohn, J. F.; Sebe, Niculae
Self-adaptive matrix completion for heart rate estimation from face videos under realistic conditions / Tulyakov, Sergey; Alameda Pineda, Xavier; Ricci, E.; Yin, L.; Cohn, J. F.; Sebe, Niculae. - (2016), pp. 2396-2404. (Intervento presentato al convegno CVPR 2016 tenutosi a Las Vegas nel 26 June-1 July 2016) [10.1109/CVPR.2016.263].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/166679
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