A robust perception based method for iris tracking

The paper presents an application of the modified kernel based object tracking to iris tracking. Human perception rules are used for defining a proper feature space for iris that mainly accounts for the fact that eyes represent instinctive visual fixation regions. In addition, a similarity metric that is close to the way human vision compares and perceives the difference between scene components has been employed for finding the exact iris location in subsequent frames. As a result, just one iteration of the mean shift algorithm allows us to get a faithful estimation of iris location in subsequent frames. This property makes the proposed algorithm implementable on mobile devices and useful for real time applications. Experimental results performed on MICHE database show that the proposed method is robust to changes in illumination or scale, iris partial or total occlusion for some subsequent frames, blinks.