Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking

doi:10.1088/1674-1056/19/10/104601

中国物理B ›› 2010, Vol. 19 ›› Issue (10): 104601-104601.doi: 10.1088/1674-1056/19/10/104601

Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking

张祖涛¹, 张家树²

(1)School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China; Sichuan Provincial Key Laboratory of Signal & Information Processing, Southwest Jiaotong University, Chengdu 610031, China; (2)Sichuan Provincial Key Laboratory of Signal & Information Processing, Southwest Jiaotong University, Chengdu 610031, China

收稿日期:2010-01-13 修回日期:2010-05-17 出版日期:2010-10-15 发布日期:2010-10-15
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No. 60971104), the Fundamental Research Funds for the Cental Universities (Grant No. SWJTU09BR092), and the Young Teacher Scientific Research Foundation of Southwest Jiaotong University (Grant No. 2009Q032).

Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking

Zhang Zu-Tao(张祖涛)^a)b)^† and Zhang Jia-Shu(张家树)^b)

^a School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China; ^b Sichuan Provincial Key Laboratory of Signal & Information Processing, Southwest Jiaotong University, Chengdu 610031, China

Received:2010-01-13 Revised:2010-05-17 Online:2010-10-15 Published:2010-10-15
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No. 60971104), the Fundamental Research Funds for the Cental Universities (Grant No. SWJTU09BR092), and the Young Teacher Scientific Research Foundation of Southwest Jiaotong University (Grant No. 2009Q032).

摘要/Abstract

摘要： The unscented Kalman filter is a developed well-known method for nonlinear motion estimation and tracking. However, the standard unscented Kalman filter has the inherent drawbacks, such as numerical instability and much more time spent on calculation in practical applications. In this paper, we present a novel sampling strong tracking nonlinear unscented Kalman filter, aiming to overcome the difficulty in nonlinear eye tracking. In the above proposed filter, the simplified unscented transform sampling strategy with n+2 sigma points leads to the computational efficiency, and suboptimal fading factor of strong tracking filtering is introduced to improve robustness and accuracy of eye tracking. Compared with the related unscented Kalman filter for eye tracking, the proposed filter has potential advantages in robustness, convergence speed, and tracking accuracy. The final experimental results show the validity of our method for eye tracking under realistic conditions.

Abstract: The unscented Kalman filter is a developed well-known method for nonlinear motion estimation and tracking. However, the standard unscented Kalman filter has the inherent drawbacks, such as numerical instability and much more time spent on calculation in practical applications. In this paper, we present a novel sampling strong tracking nonlinear unscented Kalman filter, aiming to overcome the difficulty in nonlinear eye tracking. In the above proposed filter, the simplified unscented transform sampling strategy with n+2 sigma points leads to the computational efficiency, and suboptimal fading factor of strong tracking filtering is introduced to improve robustness and accuracy of eye tracking. Compared with the related unscented Kalman filter for eye tracking, the proposed filter has potential advantages in robustness, convergence speed, and tracking accuracy. The final experimental results show the validity of our method for eye tracking under realistic conditions.

Key words: unscented Kalman filter, strong tracking filtering, sampling strong tracking nonlinear unscented Kalman filter, eye tracking

中图分类号: (Probability theory, stochastic processes, and statistics)

02.50.-r

42.30.Sy (Pattern recognition) 42.30.Va (Image forming and processing)

张祖涛, 张家树. Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking[J]. 中国物理B, 2010, 19(10): 104601-104601.

Zhang Zu-Tao(张祖涛) and Zhang Jia-Shu(张家树). Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking[J]. Chin. Phys. B, 2010, 19(10): 104601-104601.

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Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking

Sampling strong tracking nonlinear unscented Kalman filter and its application in eye tracking

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