Inproceedings
Book title :
2023 International Conference on Decision Aid Sciences and Applications (DASA)
Adresse :
Skikda, Algeria
Publisher :
Informations
Période : September 2023
Pages : 93-96
Détails
A Lossless Virtual Reality Based Alternative to Eye-Tracking for Attention Quantification
Hadri Sid Ahmed Bouramoul Abdelkrim Mota Macias José Miguel
Precise measurement of visual attention is crucial for various fields such as psychology, neuroscience, and human-computer interaction. Recent scientific literature has focused on eye-tracking techniques to quantify visual allocation or to predict it. Eye tracking is certainly an efficient and accurate technique, but it comes with a high cost and a limited context of use. In this paper, we propose a novel computational model that accurately quantifies attention allocation in a virtual reality setting. The experimental results demonstrate that our model performs seamlessly with minimum hardware requirements. Our findings suggest that this model has the potential to measure spatio-visual attention allocation accurately and reliably over extended periods, and could be a serious alternative to eye-tracking techniques in a variety of usage, such as therapy interventions.
Mots clés :
Solid modeling Visualization Computational modeling Semantics Medical treatment Virtual environments Psychology Virtual Reality Computational Model Visual Attention Attention Quantification Psychotherapy
Réf. de citation :
misc-lab-431
DOI :
10.1109/DASA59624.2023.10286755
Lien :
Texte intégral
ACM :
H. S. Ahmed, B. Abdelkrim and M. M. J. Miguel. 2023. A Lossless Virtual Reality Based Alternative to Eye-Tracking for Attention Quantification. In Proceedings of the 2023 International Conference on Decision Aid Sciences and Applications (DASA), Skikda, Algeria (September 2023), IEEE, 93-96. DOI: https://doi.org/10.1109/DASA59624.2023.10286755.
APA :
Ahmed, H. S., Abdelkrim, B. & Miguel, M. M. J. (2023, September). A Lossless Virtual Reality Based Alternative to Eye-Tracking for Attention Quantification. In Proceedings of the 2023 International Conference on Decision Aid Sciences and Applications (DASA), Skikda, Algeria, IEEE, 93-96. DOI: https://doi.org/10.1109/DASA59624.2023.10286755
IEEE :
H. S. Ahmed, B. Abdelkrim and M. M. J. Miguel, "A Lossless Virtual Reality Based Alternative to Eye-Tracking for Attention Quantification". In Proceedings of the 2023 International Conference on Decision Aid Sciences and Applications (DASA), Skikda, Algeria, IEEE, pp. 93-96, September, 2023. DOI: https://doi.org/10.1109/DASA59624.2023.10286755.
BibTeX :
@inproceedings{misc-lab-431,
author = {Ahmed, Hadri Sid and Abdelkrim, Bouramoul and Miguel, Mota MaciasJos\'{e}},
title = {A Lossless Virtual Reality Based Alternative to Eye-Tracking for Attention Quantification},
booktitle = {2023 International Conference on Decision Aid Sciences and Applications (DASA)},
location = {Skikda, Algeria},
pages = {93--96},
publisher = {IEEE},
year = {2023},
month = {September},
doi = {10.1109/DASA59624.2023.10286755},
url = {https://ieeexplore.ieee.org/document/10286755},
keywords = {Solid modeling, Visualization, Computational modeling, Semantics, Medical treatment, Virtual environments, Psychology, Virtual Reality, Computational Model, Visual Attention, Attention Quantification, Psychotherapy}
}
RIS :
TY  - CONF
TI - A Lossless Virtual Reality Based Alternative to Eye-Tracking for Attention Quantification
AU - H. S. Ahmed
AU - B. Abdelkrim
AU - M. M. J. Miguel
PY - 2023
BT - 2023 International Conference on Decision Aid Sciences and Applications (DASA), Skikda, Algeria
SP - 93
EP - 96
PB - IEEE
AB - Precise measurement of visual attention is crucial for various fields such as psychology, neuroscience, and human-computer interaction. Recent scientific literature has focused on eye-tracking techniques to quantify visual allocation or to predict it. Eye tracking is certainly an efficient and accurate technique, but it comes with a high cost and a limited context of use. In this paper, we propose a novel computational model that accurately quantifies attention allocation in a virtual reality setting. The experimental results demonstrate that our model performs seamlessly with minimum hardware requirements. Our findings suggest that this model has the potential to measure spatio-visual attention allocation accurately and reliably over extended periods, and could be a serious alternative to eye-tracking techniques in a variety of usage, such as therapy interventions.
KW - Solid modeling
KW - Visualization
KW - Computational modeling
KW - Semantics
KW - Medical treatment
KW - Virtual environments
KW - Psychology
KW - Virtual Reality
KW - Computational Model
KW - Visual Attention
KW - Attention Quantification
KW - Psychotherapy
DO - 10.1109/DASA59624.2023.10286755
UR - https://ieeexplore.ieee.org/document/10286755
ID - misc-lab-431
ER -