Facial Empathy Analysis Through Deep Learning and Computer Vision Techniques in Mixed Reality Environments

Insaf Setitra, Domitile Lourdeaux, Louenas Bounia

2025

Abstract

This paper introduces a novel approach for facial empathy analysis using deep learning and computer vision techniques within mixed reality environments. The primary objective is to detect and quantify empathic responses based on facial expressions, establishing the link between empathy and facial expressions. We propose the Deep Convolutional Neural Network with the Exponential Linear Unit activation function (ELU-DCNN). We moreover design an augmented reality platform with two main features (i). virtual overlay of a VR headset on the user’s face and (ii). facial emotion recognition for users wearing the VR headset. Our target is to analyse facial expressions in immersed environments in order to assess the empathy of users while being immersed in specific environments. Our results analyse the feasibility and effectiveness of these models in detecting and quantifying empathy through facial expressions. This work contributes to the growing field of affective computing and highlights the potential of integrating advanced computer vision techniques in mixed reality applications to better understand human emotional responses.

Paper Citation

in Harvard Style

Setitra I., Lourdeaux D. and Bounia L. (2025). Facial Empathy Analysis Through Deep Learning and Computer Vision Techniques in Mixed Reality Environments. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 31-39. DOI: 10.5220/0013057800003890

in Bibtex Style

@conference{icaart25,
author={Insaf Setitra and Domitile Lourdeaux and Louenas Bounia},
title={Facial Empathy Analysis Through Deep Learning and Computer Vision Techniques in Mixed Reality Environments},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={31-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013057800003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Facial Empathy Analysis Through Deep Learning and Computer Vision Techniques in Mixed Reality Environments
SN - 978-989-758-737-5
AU - Setitra I.
AU - Lourdeaux D.
AU - Bounia L.
PY - 2025
SP - 31
EP - 39
DO - 10.5220/0013057800003890
PB - SciTePress