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.
الكلمات المفتاحية :
Solid modeling
Visualization
Computational modeling
Semantics
Medical treatment
Virtual environments
Psychology
Virtual Reality
Computational Model
Visual Attention
Attention Quantification
Psychotherapy
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 -