Texas State University, Department of Computer Science, San Marcos, TX, 78666, USA.
Sci Data. 2023 Mar 30;10(1):177. doi: 10.1038/s41597-023-02075-5.
We present GazeBaseVR, a large-scale, longitudinal, binocular eye-tracking (ET) dataset collected at 250 Hz with an ET-enabled virtual-reality (VR) headset. GazeBaseVR comprises 5,020 binocular recordings from a diverse population of 407 college-aged participants. Participants were recorded up to six times each over a 26-month period, each time performing a series of five different ET tasks: (1) a vergence task, (2) a horizontal smooth pursuit task, (3) a video-viewing task, (4) a self-paced reading task, and (5) a random oblique saccade task. Many of these participants have also been recorded for two previously published datasets with different ET devices, and 11 participants were recorded before and after COVID-19 infection and recovery. GazeBaseVR is suitable for a wide range of research on ET data in VR devices, especially eye movement biometrics due to its large population and longitudinal nature. In addition to ET data, additional participant details are provided to enable further research on topics such as fairness.
我们展示了 GazeBaseVR，这是一个大规模的、纵向的、带有双眼追踪（ET）功能的虚拟现实（VR）头戴设备以 250Hz 的频率采集的眼动追踪数据集。GazeBaseVR 包含了来自 407 名不同年龄段的参与者的 5020 个双眼记录。参与者在 26 个月的时间里，最多每人进行了六次记录，每次进行五个不同的 ET 任务：（1）聚散任务，（2）水平平滑追随任务，（3）视频观看任务，（4）自主阅读任务，（5）随机斜向扫视任务。其中许多参与者也在之前的两个使用不同 ET 设备的数据集上进行了记录，并且有 11 名参与者在 COVID-19 感染和康复前后进行了记录。GazeBaseVR 非常适合在 VR 设备中进行广泛的 ET 数据研究，特别是眼动生物识别，因为它具有较大的人群和纵向性质。除了 ET 数据，还提供了额外的参与者详细信息，以支持有关公平性等主题的进一步研究。
