Constraint-based gaze estimation without active calibration

Existing eye gaze tracking systems typically require an explicit personal calibration process in order to estimate certain person-specific eye parameters. For natural human computer interaction, such a personal calibration is often cumbersome and unnatural. In this paper, we introduce a new method that estimates a person´s gaze without active personal calibration. By exploiting the binocular constraint that the gaze point is produced by the intersection of visual axes of two eyes and some generic person-independent constraints on eye parameters, our method is able to estimate the required person-specific parameters implicitly and naturally without active participation from the user and without use of any special calibration object. Experiments with different subjects show that the proposed method achieves good gaze estimation comparable to the conventional 9 point method.