Eye-Gaze Detection with a Single WebCAM Based on Geometry Features Extraction

In this paper, we propose an efficient approach for real-time eye-gaze detection from images acquired from a web camera. The measured data is sufficient to describe the eye movement, because the web camera is stationary with respect to the head. First, the image is binarized with a dynamic threshold. Then geometry features of the eye image are extracted from binary image. Next using estimation method based on geometry structure of eye, we detect the positions of two eye corners. After that, the center of iris is detected by matching between an iris boundary model and image contours. Finally, using the relative position information between the center of iris and the eye corners, base on the relationship between image coordinate and monitor coordinate, the position where the eye is looking at the monitor is calculated. This system requires only a low cost web camera and a personal computer. Experimental results show that the proposed system can detect accurately eye movements in real-time.