Bi-directional gaze-based communication offers an intuitive and natural way for users to interact with systems. This approach utilizes the user’s gaze not only to communicate intent but also to obtain feedback, which promotes mutual understanding and trust between the user and the system. In this review, we explore the state of the art in gaze-based communication, focusing on both directions: From user to system and from system to user. First, we examine how eye-tracking data is processed and utilized for communication from the user to the system. This includes a range of techniques for gaze-based interaction and the critical role of intent prediction, which enhances the system’s ability to anticipate the user’s needs. Next, we analyze the reverse pathway—how systems provide feedback to users via various channels, highlighting their advantages and limitations. Finally, we discuss the potential integration of these two communication streams, paving the way for more intuitive and efficient gaze-based interaction models, especially in the context of Artificial Intelligence. Our overview emphasizes the future prospects for combining these approaches to create seamless, trust-building communication between users and systems. Ensuring that these systems are designed with a focus on usability and accessibility will be critical to making them effective communication tools for a wide range of users.
Read full abstract7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access