A Webcam Artificial Intelligence-Based Gaze-Tracking Algorithm

Saul Figueroa, Israel Pineda, Paulina Vizcaíno, Iván Reyes-Chacón, Manuel Morocho-Cayamcela, Manuel Morocho-Cayamcela

2024

Abstract

Nowadays, technological advancements for supporting human-computer interaction have had a big impact. However, most of those technologies are expensive. For that reason, building a webcam gaze-tracking system represents a computationally cost-effective approach. The gaze-tracking technique focuses on tracking the gaze direction and estimating its coordinates over a computer screen to follow user visual attention. This research presents a gaze estimation approach to predict the user's gaze direction using a webcam artificial intelligence-based gaze-tracking algorithm. The purpose of this paper is to train a convolutional neural network model capable of predicting a 3D gaze vector to estimate then the 2D gaze position coordinates over a computer screen. To perform this task, three steps are followed: $1)$ Pre-processing the input, crop facial, and eye images from the MPIIFaceGaze dataset. $2)$ Train a customized network based on a ResNet-50 pre-trained on ImageNet for gaze vector predictions. $3)$ 3D gaze vectors conversion to 2D point of gaze on the screen. The results demonstrate that our model outperforms the state-of-the-art VGG-16 model under the same dataset by up to $\sim33\%$.

Paper Citation

in Harvard Style

Figueroa S., Pineda I., Vizcaíno P., Reyes-Chacón I. and Morocho-Cayamcela M. (2024). A Webcam Artificial Intelligence-Based Gaze-Tracking Algorithm. In Proceedings of the 19th International Conference on Software Technologies - Volume 1: ICSOFT; ISBN 978-989-758-706-1, SciTePress, pages 228-235. DOI: 10.5220/0012759700003753

in Bibtex Style

@conference{icsoft24,
author={Saul Figueroa and Israel Pineda and Paulina Vizcaíno and Iván Reyes-Chacón and Manuel Morocho-Cayamcela},
title={A Webcam Artificial Intelligence-Based Gaze-Tracking Algorithm},
booktitle={Proceedings of the 19th International Conference on Software Technologies - Volume 1: ICSOFT},
year={2024},
pages={228-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012759700003753},
isbn={978-989-758-706-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Software Technologies - Volume 1: ICSOFT
TI - A Webcam Artificial Intelligence-Based Gaze-Tracking Algorithm
SN - 978-989-758-706-1
AU - Figueroa S.
AU - Pineda I.
AU - Vizcaíno P.
AU - Reyes-Chacón I.
AU - Morocho-Cayamcela M.
PY - 2024
SP - 228
EP - 235
DO - 10.5220/0012759700003753
PB - SciTePress