Perceptual user interfaces using vision-based eye tracking

Authors:
Ravikrishna Ruddarraju;Antonio Haro;Kris Nagel;Quan T. Tran;Irfan A. Essa;Gregory Abowd;Elizabeth D. Mynatt
Affiliations:
School of Electrical and Computer Engineering, Atlanta, GA;GVU Center, College of Computing Georgia Institute of Technology, Atlanta, GA;GVU Center, College of Computing Georgia Institute of Technology, Atlanta, GA;GVU Center, College of Computing Georgia Institute of Technology, Atlanta, GA;GVU Center, College of Computing Georgia Institute of Technology, Atlanta, GA;GVU Center, College of Computing Georgia Institute of Technology, Atlanta, GA;GVU Center, College of Computing Georgia Institute of Technology, Atlanta, GA
Venue:
Proceedings of the 5th international conference on Multimodal interfaces
Year:
2003

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Abstract

We present a multi-camera vision-based eye tracking method to robustly locate and track user's eyes as they interact with an application. We propose enhancements to various vision-based eye-tracking approaches, which include (a) the use of multiple cameras to estimate head pose and increase coverage of the sensors and (b) the use of probabilistic measures incorporating Fisher's linear discriminant to robustly track the eyes under varying lighting conditions in real-time. We present experiments and quantitative results to demonstrate the robustness of our eye tracking in two application prototypes.