GazeBaseVR Data Repository

Lohr, Dillon;Aziz, Samantha;Friedman, Lee;Komogortsev, Oleg

Description

GazeBaseVR is 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 some 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. For more details regarding the experimental methodology, please refer to the corresponding manuscript.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.5

FAIR Score

85%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

figshare

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Human-Computer Interaction

Field

Computer Science

Domain

Physical Sciences

Confidence Score

66%

Source

Open Alex

Keywords

Human-computer interactionVirtual and mixed reality

Normalization Factors

FT

57.69

CTw

1.00

MTw

1.00