Multiple states and joint objects particle filter for eye tracking

Jin Xiong; Huanqing Feng

doi:10.1117/12.750700

15 November 2007 Multiple states and joint objects particle filter for eye tracking

Jin Xiong, Huanqing Feng

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67863X (2007) https://doi.org/10.1117/12.750700
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Recent works have proven that the particle filter is a powerful tracking technique for non-linear and non-Gaussian estimation problem. This paper presents an extension algorithm based on the color-based particle filter framework, which is applicable for complex eye tracking because of two main innovations. Firstly, an employment of an extra discrete-value variable and its associated transition probability matrix (TPM) makes it feasible in tracking multiple states of the eye during blinking. Secondly, the joint-object thought used in state vector eliminates the distraction from eyes to each other. The experimental results illustrate that the proposed algorithm is efficient for eye tracking.

Citation Download Citation

Jin Xiong and Huanqing Feng "Multiple states and joint objects particle filter for eye tracking", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67863X (15 November 2007); https://doi.org/10.1117/12.750700

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