Directed or Guided? Classification of Gaze Attention Shifts based on Eye and Head Movement ETRA002

Gaze can be directed at will, or guided by objects that draw our attention. We propose classifying gaze shifts as either directed or guided, since these two forms of attention have different implications for HCI. Directed attention may serve as stronger indicator of users’ planning and intent, whereas guided attention reflects interface efficacy in guiding information acquisition. We introduce a method based on eye and head movement features during gaze shifts, using data collected in virtual reality to train and evaluate a machine learning model, which we then validate in application to visual search. Our results show that this classification is both feasible and practical, extending established uses of eye tracking in HCI. This is significant because it enables a new level of analysis of visual attention.