Deep learning for eye-gaze event detection for personalized gaze-based interaction in real-world settings

Abstract

The paper presents a review of modern machine learning and, specifically, deep learning approaches to the detection of various oculomotor events. The prospects and limitations imposed by such approaches are discussed. The conditions and tasks in which these approaches prove most productive are described. The described methods can significantly refine the dynamics of visual attention and the perceptual process in general within various experimental psychological tasks. Implementing such methods in research practice will allow for more accurate description and interpretation of results obtained in specific psychological and psychophysiological studies involving the registration of oculomotor activity.

Keywords: : Perception, Eye Tracking, Machine Learning, Deep Learning

DOI: 10.54941/ahfe1007532