@article {pub4799,
	title = {Gaze-based intention estimation: principles, methodologies, and applications in HRI},
	author = {Anna Belardinelli},
	year = {2024},
	month = {April},
	abstract = {Intention prediction has become a relevant field of research in Human-Machine and Human-Robot Interaction. Indeed, any artificial
system (co)-operating with and along humans, designed to assist and coordinate its actions with a human partner, needs first to infer
the human{\textquoteright}s current intention. To spare the user the cognitive burden of explicitly uttering their goals, this inference relies mostly
on behavioral cues deemed indicative of the current action. Eye movements have long been known to be highly predictive of the
cognitive agenda unfolding during different tasks and constitute, hence, the earliest and most reliable cue for intention recognition.
Starting from the cognitive principles underlying the relationship between intentions, eye movements, and action, we review here the
state-of-the-art literature about the use of eye tracking and gaze-based models for intent recognition, the prevalent methodologies and
their applications in diverse contexts, as well as related human factors issues to be considered.},
	publisher = {ACM},
	url = {https://dl.acm.org/doi/10.1145/3656376},
	journal = {ACM Transactions on Human-Robot Interaction},
	editor = {ACM}
}