论文标题
凉亭：一个大规模的多刺，纵向眼动数据集
GazeBase: A Large-Scale, Multi-Stimulus, Longitudinal Eye Movement Dataset
论文作者
论文摘要
该手稿介绍了Gazebase，这是一个大规模的纵向数据集，其中包含来自322名大学生学科的12,334个单眼手动录音。在每轮录制期间，受试者在两个连续的会话中完成了七个任务的电池，包括a -1）固定任务，2）水平扫视任务，3）随机倾斜扫视任务，4）阅读任务，5/6）免费观看电影视频任务和7）凝视驱动的游戏游戏。在37个月的时间内，总共进行了九轮记录，随后的每一轮比赛中只有从前一轮招募的受试者。所有数据均以1,000 Hz采样率使用Eyelink 1000眼镜跟踪器收集，并在每个任务之前执行校准和验证协议，以确保数据质量。由于其大量受试者和纵向性质，阳ebase非常适合探索眼睛运动生物识别技术中的研究假设，以及将机器学习技术应用于眼动信号分析的其他新兴应用。
This manuscript presents GazeBase, a large-scale longitudinal dataset containing 12,334 monocular eye-movement recordings captured from 322 college-aged subjects. Subjects 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. A total of nine rounds of recording were conducted over a 37 month period, with subjects in each subsequent round recruited exclusively from the prior round. 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 subjects and longitudinal nature, GazeBase is well suited for exploring research hypotheses in eye movement biometrics, along with other emerging applications applying machine learning techniques to eye movement signal analysis.
