A strong tracking nonlinear robust filter for eye tracking

Abstract

Non-intrusive methods for eye tracking are important for many applications of vision-based human computer interaction. However, due to the high nonlinearity of eye motion, how to ensure the robustness of external interference and accuracy of eye tracking pose the primary obstacle to the integration of eye movements into today’s interfaces. In this paper, we present a strong tracking unscented Kalman filter (ST-UKF) algorithm, aiming to overcome the difficulty in nonlinear eye tracking. In the proposed ST-UKF, the Suboptimal fading factor of strong tracking filtering is introduced to improve robustness and accuracy of eye tracking. Compared with the related Kalman filter for eye tracking, the proposed ST-UKF has potential advantages in robustness and tracking accuracy. The last experimental results show the validity of our method for eye tracking under realistic conditions.