Implicit User Calibration for Model-based Gaze-tracking System using Face Detection around Optical Axis of Eye

In recent studies of gaze tracking system using 3D model-based methods, the optical axis of the eye is estimated without user calibration. The remaining problem for achieving implicit user calibration is to estimate the difference between the optical axis and visual axis of the eye (angle kappa). In this paper, we propose an implicit user calibration method using face detection around the optical axis of the eye. We assume that the peak of the average of face region images indicates the visual axis of the eye in the eye coordinate system. The angle kappa is estimated as the difference between the optical axis of the eye and the peak of the average of face region images. We developed a prototype system with two cameras and two IR-LEDs. The experimental results showed that the proposed method can estimate the angle kappa more accurately than the method that uses Itti's saliency map instead of face detection.