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BY-NC-ND 4.0 license Open Access Published by De Gruyter September 7, 2017

Heart rate from face videos under realistic conditions for advanced driver monitoring

  • Christian S. Pilz EMAIL logo , Sebastian Zaunseder , Ulrich Canzler and Jarek Krajewski

Abstract

The role of physiological signals has a large impact on driver monitoring systems, since it tells something about the human state. This work addresses the recursive probabilistic inference problem in time-varying linear dynamic systems to incorporate invariance into the task of heart rate estimation from face videos under realistic conditions. The invariance encapsulates motion as well as varying illumination conditions in order to accurately estimate vitality parameters from human faces using conventional camera technology. The solution is based on the canonical state space representation of an Itô process and a Wiener velocity model. Empirical results yield to excellent real-time and estimation performance of heart rates in presence of disturbing factors, like rigid head motion, talking, facial expressions and natural illumination conditions making the process of human state estimation from face videos applicable in a much broader sense, pushing the technology towards advanced driver monitoring systems.

Published Online: 2017-09-07

©2017 Christian S. Pilz et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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