A Lossless Virtual Reality Based Alternative to Eye-Tracking for Attention Quantification

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.