A novel strong tracking finite-difference extended Kalman filter for nonlinear eye tracking  

作　　者：ZHANG ZuTao ZHANG JiaShu 

机构地区：[1]School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China [2]Sichuan Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, China

出　　处：《Science in China(Series F)》2009年第4期688-694,共7页中国科学（F辑英文版）

基　　金：Supported by the National Natural Science Foundation of China (Grant No. 60572027);the Outstanding Young Researchers Foundation of Sichuan Province (Grant No. 03ZQ026-033);the Program for New Century Excellent Talents in University of China (Grant No. NCET-05-0794);the Young Teacher Foundation of Mechanical School (Grant No. MYF0806)

摘　　要：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 robust- ness of external interference and accuracy of eye tracking poses the primary obstacle to the integration of eye movements into today＇s interfaces. In this paper, we present a strong tracking finite-difference extended Kalman filter algorithm, aiming to overcome the difficulty in modeling nonlinear eye tracking. In filtering calculation, strong tracking factor is introduced to modify a priori covariance matrix and improve the accuracy of the filter. The filter uses finite-difference method to calculate partial derivatives of nonlinear functions for eye tracking. The latest experimental results show the validity of our method for eye tracking under realistic conditions.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 robust- ness of external interference and accuracy of eye tracking poses the primary obstacle to the integration of eye movements into today＇s interfaces. In this paper, we present a strong tracking finite-difference extended Kalman filter algorithm, aiming to overcome the difficulty in modeling nonlinear eye tracking. In filtering calculation, strong tracking factor is introduced to modify a priori covariance matrix and improve the accuracy of the filter. The filter uses finite-difference method to calculate partial derivatives of nonlinear functions for eye tracking. The latest experimental results show the validity of our method for eye tracking under realistic conditions.

关 键 词：strong tracking finite-difference extended Kalman filter （STFDEKF） eye tracking extended Kalman filter （EKF） suboptimal fadingfactor 

分 类 号：O174.41[理学—数学] TN953[理学—基础数学]