<title>Automatic eye tracking in video image sequence</title>

Abstract

A new algorithm is developed to implement automatic eye tracking without prior reference model and prior knowledge of size, orientation, shape, color and other data for the human eyes. The algorithm is based on the analysis of the eye features in eye contrast, eye blinking, and other properties. It consists of two stages. In the initialization stage the algorithm locates the approximate head location from two consecutive video frames. The size of three same size blocks is determined. They are used to detect the left and right eyes. Two eyes are symmetric and blink simultaneously at all the time. The algorithm extracts the similarity features of two eyes and dissimilarity of eyes from the region between eyes which is represented by middle block. The measures are implemented by the analysis of correlation and horizontal contrast property. The algorithm is able to detect the eye status of blinking eyes and closed eye for a period of time in a video frame sequence. This algorithm is a dynamic automatic eye tracking system that can adapt the environment change and reinitialize if the tracking is lost. The experiments of this method show satisfactory results in term of accuracy and reasonable time complexity. It shows that the method can be applied to eye tracking regardless of skin color, orientation of head, size of head, background changing, or other constraints. The experiments are conducted in targeting to a moving head by 20 frames/second video sequence.