Most eye trackers work well for open eyes. However, blinking is a physiological necessity for humans. Moreover, for applications such as facial expression analysis and driver awareness systems, we need to do more than tracking the locations of the person's eyes but obtain their detailed description. We need to recover the state of the eyes (i.e. whether they are open or closed), and the parameters of an eye model (e.g. the location and radius of the iris, and the corners and height of the eye opening). In this paper, we develop a dual-state model based system of tracking eye features that uses convergent tracking techniques and show how it can be used to detect whether the eyes are open or closed, and to recover the parameters of the eye model. Processing speed on a Pentium II 400MHZ PC is approximately 3 frames/second. In experimental tests on 500 image sequences from child and adult subjects with varying colors of skin and eye, accurate tracking results are obtained in 98% of image sequences.