Estimation of the Cardiac Pulse from Facial Video in Realistic Conditions

Arvind Subramaniam, K. Rajitha

2019

Abstract

Remote detection of the cardiac pulse has a number of applications in fields of sports and medicine, and can be used to determine an individual’s physiological state. Over the years, several papers have proposed a number of approaches to extract heart rate (HR) using video imaging. However, all these approaches have employed the Viola-Jones algorithm for face detection. Additionally, these methods usually require the subject to be stationary and do not take illumination changes into account. The present research proposes a novel framework that employs Faster RCNNs (Region-based Convolutional Neural Networks) for face detection, followed by face tracking using the Kanade-Lukas-Tomasi (KLT) algorithm. In addition, the present framework recovers the feature points which are lost during extreme head movements of the subject. Our method is robust to extreme motion interferences (head movements) and utilizes Recursive Least Square (RLS) adaptive filtering methods to tackle interferences caused by illumination variations. The accuracy of the model has been tested based on a movie evaluation scenario and the accuracy was estimated on a public database MAHNOB-HCI. The output of the performance measure showed that the present model outperforms previously proposed methods.

Paper Citation

in Harvard Style

Subramaniam A. and Rajitha K. (2019). Estimation of the Cardiac Pulse from Facial Video in Realistic Conditions.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 145-153. DOI: 10.5220/0007367801450153

in Bibtex Style

@conference{icaart19,
author={Arvind Subramaniam and K. Rajitha},
title={Estimation of the Cardiac Pulse from Facial Video in Realistic Conditions},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2019},
pages={145-153},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007367801450153},
isbn={978-989-758-350-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Estimation of the Cardiac Pulse from Facial Video in Realistic Conditions
SN - 978-989-758-350-6
AU - Subramaniam A.
AU - Rajitha K.
PY - 2019
SP - 145
EP - 153
DO - 10.5220/0007367801450153