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.