Combining Kalman filtering and mean shift for real time eye tracking under active IR illumination

Most eye trackers based on active IR illumination require distinctive bright pupil effect to work well. In this paper, we present a new real time eye tracking methodology that works under variable and realistic lighting conditions and various face orientations. By combining the conventional appearance based object recognition method (SVM) and object tracking method (mean shift) with Kalman filtering based on active IR illumination, our technique is able to benefit from the strengths of different techniques and overcome their respective limitations. Experimental study shows significant improvement of our technique over the existing techniques.