GazeBase, a large-scale, multi-stimulus, longitudinal eye movement dataset

Autor: Evgeniy Abdulin, Oleg V. Komogortsev, Henry Griffith, Dillon J. Lohr
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Adult
Male
FOS: Computer and information sciences
Statistics and Probability
Data Descriptor
Adolescent
Eye Movements
Computer science
Science
0211 other engineering and technologies
Computer Science - Human-Computer Interaction
02 engineering and technology
Library and Information Sciences
050105 experimental psychology
Pupil
Human-Computer Interaction (cs.HC)
Education
Task (project management)
Young Adult
Humans
0501 psychology and cognitive sciences
Computer vision
Longitudinal Studies
Eye-Tracking Technology
021110 strategic
defence & security studies
Monocular
business.industry
05 social sciences
Eye movement
Middle Aged
Electrical and electronic engineering
Computer Science Applications
Reading
Data quality
Saccade
Fixation (visual)
Eye tracking
Female
Artificial intelligence
Statistics
Probability and Uncertainty
business
Information Systems
Zdroj: Scientific Data, Vol 8, Iss 1, Pp 1-9 (2021)
Scientific Data
ISSN: 2052-4463
1476-1866
Popis: This manuscript presents GazeBase, a large-scale longitudinal dataset containing 12,334 monocular eye-movement recordings captured from 322 college-aged participants. Participants completed a battery of seven tasks in two contiguous sessions during each round of recording, including a – (1) fixation task, (2) horizontal saccade task, (3) random oblique saccade task, (4) reading task, (5/6) free viewing of cinematic video task, and (7) gaze-driven gaming task. Nine rounds of recording were conducted over a 37 month period, with participants in each subsequent round recruited exclusively from prior rounds. All data was collected using an EyeLink 1000 eye tracker at a 1,000 Hz sampling rate, with a calibration and validation protocol performed before each task to ensure data quality. Due to its large number of participants and longitudinal nature, GazeBase is well suited for exploring research hypotheses in eye movement biometrics, along with other applications applying machine learning to eye movement signal analysis. Classification labels produced by the instrument’s real-time parser are provided for a subset of GazeBase, along with pupil area.
Measurement(s) eye movement measurement Technology Type(s) eye tracking device Factor Type(s) round • participant Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14761866
Databáze: OpenAIRE
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