Researchers Compile 20 Million Images of Eyes in a Massive Open-Source Dataset
AI and Data Science Newsposted by ODSC Team February 10, 2021 ODSC Team
Countless modern applications use eye-tracking software or rely on the user’s eyes. Whether it’s for AR/VR gaming or for helping people with disabilities, there’s much to be done with eye data. Enter TEyeD, a public data set with over 20 million images of eyes collected from a team of researchers at University Tübingen, Germany, who hope to see some good come from possibilities of eye-tracking devices in their paper, “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.”
The TEyeD data set was created using seven different head-mounted eye trackers across a variety of situations. Two of them were placed into virtual reality and augmented reality devices.
The 20 million images weren’t just taken in a lab at various angles, rather, they were obtained through a variety of tasks, such as in car rides, simulator rides, outdoor sports activities, and daily indoor activities. The data set includes 2D\&3D landmarks, semantic segmentation, 3D eyeball annotation, and the gaze vector and eye movement types for all images. For the videos, they range from mere seconds to multiple hours.
Many applications and devices use eye-tracking software, so this open-source dataset, TEyeD, will be a welcome (and massive) boon to other researchers. Human eye movements affect so much – more than just what we’re looking at right now. Some devices can be used for fun, such as with AR and VR games, while other applications can be life-saving, such as with tools to help those with disabilities.
The dataset is available here.
More on eye tracking, healthcare, and unique use cases beyond TEyeD:
This research is certainly insightful, but it doesn’t stand on its own. To make use of it, you need to know more about use cases, human-computer interaction, and the various disciplines where this data might be useful. Here are some Ai+ Training sessions that may prove valuable:
Playlist: Ai and Healthcare, Life Science, Pharma, and Biotech
Introduction To Face Processing With Computer Vision
Deep Transfer Learning for Computer Vision: Real-World Applications at Nanoscale
There are also a few relevant talks coming to ODSC East 2021 this March 30th-April 1st that may prove useful as well:
AI-Powered Best Healthcare for Everyone
The Clinician’s AI Partner: Augmenting Clinician Capabilities Across the Spectrum of Healthcare