Real-Time CNN Based Facial Emotion Recognition Model for a Mobile Serious Game

Carolain Anto-Chavez, Richard Maguiña-Bernuy, Willy Ugarte

2024

Abstract

Every year, the increase in human-computer interaction is noticeable. This brings with it the evolution of computer vision to improve this interaction to make it more efficient and effective. This paper presents a CNN-based emotion face recognition model capable to be executed on mobile devices, in real time and with high accuracy. Different models implemented in other research are usually of large sizes, and although they obtained high accuracy, they fail to make predictions in an optimal time, which prevents a fluid interaction with the computer. To improve these, we have implemented a lightweight CNN model trained with the FER-2013 dataset to obtain the prediction of seven basic emotions. Experimentation shows that our model achieves an accuracy of 66.52% in validation, can be stored in a 13.23MB file and achieves an average processing time of 14.39ms and 16.06ms, on a tablet and a phone, respectively.

Paper Citation

in Harvard Style

Anto-Chavez C., Maguiña-Bernuy R. and Ugarte W. (2024). Real-Time CNN Based Facial Emotion Recognition Model for a Mobile Serious Game. In Proceedings of the 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE; ISBN 978-989-758-700-9, SciTePress, pages 84-92. DOI: 10.5220/0012683800003699

in Bibtex Style

@conference{ict4awe24,
author={Carolain Anto-Chavez and Richard Maguiña-Bernuy and Willy Ugarte},
title={Real-Time CNN Based Facial Emotion Recognition Model for a Mobile Serious Game},
booktitle={Proceedings of the 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE},
year={2024},
pages={84-92},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012683800003699},
isbn={978-989-758-700-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE
TI - Real-Time CNN Based Facial Emotion Recognition Model for a Mobile Serious Game
SN - 978-989-758-700-9
AU - Anto-Chavez C.
AU - Maguiña-Bernuy R.
AU - Ugarte W.
PY - 2024
SP - 84
EP - 92
DO - 10.5220/0012683800003699
PB - SciTePress