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.

翻译：已有研究表明，以1000Hz频率记录的眼动数据可用于个体身份认证。本研究通过利用支持眼动追踪的虚拟现实头显采集的数据集（GazeBaseVR），探讨眼动生物特征的效能，并将其与下采样至250Hz的高端眼动追踪器数据集（GazeBase）的性能进行对比。同时，研究旨在评估双眼与单眼眼动数据的生物特征潜力。GazeBaseVR数据集在双眼配置下实现了1.67%的等错误率，以及在10^-4误接受率下22.73%的错误拒绝率。本研究证实了从支持眼动追踪的VR头显获取数据的生物特征可行性。