Eye Tracking for Identification
Peter Bufdinger · 2024
This study explores how users can be differentiated by analyzing natural gaze behavior while freely looking at images. The approach is based on the observation that looking at different images induces unique emotional responses reflected in gaze behavior. By collecting gaze data, the authors demonstrate the potential of identifying different people using machine learning. This paves the way for authentication methods based on natural human gaze behavior.