One-time calibration eye gaze detection system

This paper describes a real-time infrared-based system for eye gaze tracking. Most of the existing gaze tracking systems require a cumbersome calibration process every time an user operates the system and work well only with small head movement. Our system is simpler as it requires only one-time calibration for each user and the calibration data is stored for subsequent reuse. Besides that, our system can perform robust and accurate gaze estimation under rather significant head pose variations. This is made possible by a gaze calibration procedure which maps the pupil and glint parameters to screen coordinates using the Radial Basis Function Neural Network (RBFNN). Our system currently has a spatial gaze resolution of about 3 degrees and it operates at 25 fps with an average accuracy of 90% for gaze estimation.