Face and eye tracking algorithm based on digital image processing

A non-invasive interface to track eye position using digital image processing techniques is under development. Information about head and eye position is obtained from digital images. The objective is to develop an interface to detect eye position based only on digital image processing algorithms, free of electrodes or other electronic devices. We propose a method for eye tracking built into five stages. These include: coarse and fine face detection, finding the eye region of maximum probability, map of the pupil/iris location and pupil/iris detection. Using frontal face images obtained from a database, the probability maps for the eye region were built. Only gray levels are considered for this computation (8 bits). The algorithms for face and eye detection were assessed on 102 images from the Purdue database and on 897 images from a video sequence. The face detection algorithm reached a 99% and 100% correct detection rate on the databases respectively. On the same databases the pupil/iris detection algorithm reached 85.3% and 98.4% of correct detection respectively.