Strengthening Security in Industrial Settings: A Study on Gaze-Based Biometrics through Free Observation of Static Images
Marco Porta, Alessandro Barboni · 2019
As security becomes crucial in an increasing number of industrial contexts, the need arises for new ways to check or authenticate the identity of people. In this paper, we present a method that exploits gaze data to implement a soft biometric technique. Specifically, the user's gaze behavior is inspected during the unconstrained observation of different kinds of static images. The obtained results, achieved using a machine learning approach, are generally satisfying, although more experiments will be necessary to fully confirm the viability of the proposed method.