AUTHOR=Wang Chen , Pun Thierry , Chanel Guillaume 

TITLE=A Comparative Survey of Methods for Remote Heart Rate Detection From Frontal Face Videos

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 6 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2018.00033

DOI=10.3389/fbioe.2018.00033

ISSN=2296-4185

ABSTRACT=Remotely measuring physiological activity can provide substantial benefits for both the medical and affective computing applications. Recent research has proposed different methodologies for the unobtrusive detection of heart rate using human face recordings. These methods are based on subtle color changes or motions of the face due to cardiovascular activities, which are invisible to human eyes but can be captured by digital cameras. Several approaches have been proposed such as signal processing and machine learning. However these methods are compared on different datasets and there is consequently no consensus on method performance. In this paper, we describe and evaluate several methods defined in literature, from 2008 until present day, for the remote detection of heart rate using human face recordings. The general heart rate processing pipeline is divided into three stages: face video processing, face blood volume pulse signal extraction and heart rate computation. Approaches presented in the paper are classified and grouped according to each stage. At each stage, algorithms are analyzed and compared based on their performance using the public database MAHNOB - HCI. Results found in this paper are limited on MAHNOB -HCI dataset and show that extracted face skin area contains more blood volume pulse information. Blind source separation and peak detection methods are more robust with head motions for estimating heart rate.