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Seminar: Providing Privacy for Eye-Tracking Data with Applications in XR

Brendan David-John

Ph.D. Candidate at the University of Florida

Thursday, January 20, 2022
10:00 AM
1100 Torgersen Hall


Eye-tracking sensors track where a user looks and are being increasingly integrated into mixed-reality devices. Although critical applications are being enabled, there are significant possibilities for violating user security and privacy expectations. There is an appreciable risk of unique user identification from eye-tracking camera images and the resulting eye movement data. Biometric identification would allow an app to connect a user’s personal ID with their work ID without needing their consent, for example.  Solutions were explored to address concerns related to the leaking of biometric features through eye-tracking data streams. Privacy mechanisms are introduced to reduce the risk of biometric recognition while still enabling applications of eye-tracking data streams. Gaze data streams can thus be made private while still allowing for applications key to the future of mixed-reality technology, such as animating virtual avatars or prediction models necessary for foveated rendering.


Brendan David-John (he/him/his) has a BS/MS from the Rochester Institute of Technology and is currently a Ph.D. candidate at the University of Florida studying Computer Science. He is from Salamanca, NY, which is located on the Allegany Reservation of the Seneca Nation of Indians. David-John’s personal goals include increasing the representation of Native Americans in STEM and higher education, specifically in computing. David-John’s research interests include eye tracking, privacy, mixed reality, and computer graphics.