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Proceedings Paper

Multiple states and joint objects particle filter for eye tracking
Author(s): Jin Xiong; Huanqing Feng
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Paper 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.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67863X (15 November 2007); doi: 10.1117/12.750700
Show Author Affiliations
Jin Xiong, Univ. of Science and Technology of China (China)
Huanqing Feng, Univ. of Science and Technology of China (China)


Published in SPIE Proceedings Vol. 6786:
MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition

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