TEyeD: Over 20 million real-world eye images with Pupil, Eyelid, and Iris 2D and 3D Segmentations, 2D and 3D Landmarks, 3D Eyeball, Gaze Vector, and Eye Movement Types
Wolfgang Fuhl, Gjergji Kasneci, Enkelejda Kasneci
TL;DR
TEyeD is the largest publicly available dataset of eye images from various head-mounted devices, including detailed annotations like landmarks, segmentation, and gaze data, supporting research in eye tracking and gaze estimation.
Contribution
This paper introduces TEyeD, a comprehensive dataset with over 20 million annotated eye images from diverse devices and activities, filling a gap in resources for VR and AR eye tracking research.
Findings
Largest dataset with 20 million images
Includes 2D/3D landmarks and segmentation
Supports VR/AR eye tracking research
Abstract
We present TEyeD, the world's largest unified public data set of eye images taken with head-mounted devices. TEyeD was acquired with seven different head-mounted eye trackers. Among them, two eye trackers were integrated into virtual reality (VR) or augmented reality (AR) devices. The images in TEyeD were obtained from various tasks, including car rides, simulator rides, outdoor sports activities, and daily indoor activities. The data set includes 2D and 3D landmarks, semantic segmentation, 3D eyeball annotation and the gaze vector and eye movement types for all images. Landmarks and semantic segmentation are provided for the pupil, iris and eyelids. Video lengths vary from a few minutes to several hours. With more than 20 million carefully annotated images, TEyeD provides a unique, coherent resource and a valuable foundation for advancing research in the field of computer vision, eye…
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