Error characterization and compensation in eye tracking systems

Abstract

The development of systems that track the eye while allowing head movement is one of the most challenging objectives of gaze tracking researchers. Tracker accuracy decreases as the subject moves from the calibration position and is especially influenced by changes in depth with respect to the screen. In this paper, we demonstrate that the pattern of error produced due to user movement mainly depends on the system configuration and hardware element placement rather than the user. Thus, we suggest alternative calibration techniques for error reduction that compensate for the lack of accuracy due to subject movement. Using these techniques, we can achieve an error reduction of more than 50%.