Evaluating Eye Movement Biometrics in Virtual Reality: A Comparative Analysis of VR Headset and High-End Eye-Tracker Collected Dataset

TL;DR

This study compares eye movement biometrics from VR headsets and high-end eye trackers, demonstrating the biometric viability of VR-based data with promising accuracy metrics.

Contribution

It provides a comparative analysis of biometric performance between VR headset and high-end eye tracker data, highlighting the potential of VR for biometric authentication.

Findings

VR headset data achieves 1.67% EER

Binocular data yields 22.73% FRR at 10^-4 FAR

VR eye-tracking data shows biometric viability

Abstract

Previous studies have shown that eye movement data recorded at 1000 Hz can be used to authenticate individuals. This study explores the effectiveness of eye movement-based biometrics (EMB) by utilizing data from an eye-tracking (ET)-enabled virtual reality (VR) headset (GazeBaseVR) and compares it to the performance using data from a high-end eye tracker (GazeBase) that has been downsampled to 250 Hz. The research also aims to assess the biometric potential of both binocular and monocular eye movement data. GazeBaseVR dataset achieves an equal error rate (EER) of 1.67% and a false rejection rate (FRR) at 10^-4 false acceptance rate (FAR) of 22.73% in a binocular configuration. This study underscores the biometric viability of data obtained from eye-tracking-enabled VR headset.