With advancements in hardware, high-quality HMD devices are being developed by numerous companies, driving increased consumer interest in AR, VR, and MR applications. In this work, we present a new dataset, called VRBiom, of periocular videos acquired using a Virtual Reality headset. The VRBiom, targeted at biometric applications, consists of 900 short videos acquired from 25 individuals recorded in the NIR spectrum. These 10s long videos have been captured using the internal tracking cameras of Meta Quest Pro at 72 FPS. To encompass real-world variations, the dataset includes recordings under three gaze conditions: steady, moving, and partially closed eyes. We have also ensured an equal split of recordings without and with glasses to facilitate the analysis of eye-wear. These videos, characterized by non-frontal views of the eye and relatively low spatial resolutions (400 x 400), can be instrumental in advancing state-of-the-art research across various biometric applications. The VRBiom dataset can be utilized to evaluate, train, or adapt models for biometric use-cases such as iris and/or periocular recognition and associated sub-tasks such as detection and semantic segmentation. In addition to data from real individuals, we have included around 1100 PA constructed from 92 PA instruments. These PAIs fall into six categories constructed through combinations of print attacks (real and synthetic identities), fake 3D eyeballs, plastic eyes, and various types of masks and mannequins. These PA videos, combined with genuine (bona-fide) data, can be utilized to address concerns related to spoofing, which is a significant threat if these devices are to be used for authentication. The VRBiom dataset is publicly available for research purposes related to biometric applications only.

翻译：随着硬件技术的进步，众多公司正在开发高质量的头戴式显示器设备，这推动了消费者对增强现实、虚拟现实和混合现实应用日益增长的兴趣。本研究提出了一个名为VRBiom的新型数据集，包含使用虚拟现实头戴设备采集的眼周视频。该数据集专为生物识别应用设计，由25位个体在近红外光谱下录制的900段短视频构成。这些时长为10秒的视频以72帧/秒的帧率通过Meta Quest Pro内置追踪摄像头采集。为涵盖真实场景中的变化，数据集包含三种注视条件下的录制：稳定注视、移动注视及部分闭眼状态。我们还确保了佩戴眼镜与未佩戴眼镜的录制视频数量均衡，以促进眼镜因素的分析。这些视频具有非正面眼部视角和相对较低空间分辨率（400×400）的特点，可有力推动各类生物识别应用的前沿研究。VRBiom数据集可用于评估、训练或适配生物识别应用模型，例如虹膜和/或眼周识别，以及相关的检测与语义分割等子任务。除真实个体数据外，我们还纳入了由92种呈现攻击工具构建的约1100个呈现攻击样本。这些呈现攻击样本通过印刷攻击（真实与合成身份）、仿制3D眼球、塑料眼球以及各类面具和人偶的组合，分为六个类别。这些呈现攻击视频与真实生物特征数据结合，可用于应对欺骗攻击相关问题——若此类设备用于身份认证，欺骗攻击将构成重大威胁。VRBiom数据集现公开提供，仅限用于生物识别应用的相关研究。