122. continuous self-calibrating eye gaze tracking for virtual reality systems

Department: Electrical & Computer Engineering
Research Institute Affiliation: California Institute for Telecommunications and Information Technology (Calit2)
Faculty Advisor(s): Truong Nguyen | Serge J. Belongie

Primary Student
Name: Subarna Tripathi
Email: stripath@ucsd.edu
Phone: 858-999-5306
Grad Year: 2017

Abstract
Most eye tracking systems require an initial calibration phase, where the user fixates their gaze at target points. This is inconvenient since it must be done every time the headset is put on. The calibration also rapidly drifts due to movement of the headset with respect to the head. We present a novel, automatic eye gaze tracking scheme inspired by smooth pursuit eye motion while playing mobile games or watching virtual reality contents. The algorithm continuously calibrates an eye tracking system for a head mounted display. This eliminates the need for an explicit calibration step and automatically compensates for small movements of the headset with respect to the head. The algorithm finds correspondences between corneal motion and screen-space motion, and uses them to generate Gaussian Process Regression(GPR) models. A combination of those models provides a continuous mapping from corneal position to screen space position. Accuracy is nearly as good as achieved with an explicit calibration step.

Industry Application Area(s)
Internet, Networking, Systems | Software, Analytics

Related Links:

  1. https://arxiv.org/abs/1612.06919

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