Facial Expression Recognition System for Stress Detection with Deep Learning

José Almeida, Fátima Rodrigues

2021

Abstract

Stress is the body's natural reaction to external and internal stimuli. Despite being something natural, prolonged exposure to stressors can contribute to serious health problems. These reactions are reflected not only physiologically, but also psychologically, translating into emotions and facial expressions. Based on this, we developed a proof of concept for a stress detector. With a convolutional neural network capable of classifying facial expressions, and an application that uses this model to classify real-time images of the user's face and thereby assess the presence of signs of stress. For the creation of the classification model was used transfer learning together with fine-tuning. In this way, we took advantage of the pre-trained networks VGG16, VGG19, and Inception-ResNet V2 to solve the problem at hand. For the transfer learning process two classifier architectures were considered. After several experiments, it was determined that VGG16, together with a classifier based on a convolutional layer, was the candidate with the best performance at classifying stressful emotions. The results obtained are very promising and the proposed stress-detection system is non-invasive, only requiring a webcam to monitor the user's facial expressions.

Paper Citation

in Harvard Style

Almeida J. and Rodrigues F. (2021). Facial Expression Recognition System for Stress Detection with Deep Learning. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-509-8, pages 256-263. DOI: 10.5220/0010474202560263

in Bibtex Style

@conference{iceis21,
author={José Almeida and Fátima Rodrigues},
title={Facial Expression Recognition System for Stress Detection with Deep Learning},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2021},
pages={256-263},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010474202560263},
isbn={978-989-758-509-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Facial Expression Recognition System for Stress Detection with Deep Learning
SN - 978-989-758-509-8
AU - Almeida J.
AU - Rodrigues F.
PY - 2021
SP - 256
EP - 263
DO - 10.5220/0010474202560263