Two-step approach for real-time eye tracking with a new filtering technique

Head and face detection and eye tracking in real time are the first steps for head gesture recognition and/or face expression recognition for a human-computer interaction interface. We propose a two-step approach for eye tracking in video streams. First, we detect or track a point between the eyes. For this task, we apply a special filter that we have proposed previously (Proc. IEEE 4th Int. Conf. on Automatic Face and Gesture Recognition, pp. 40-45, 2000). Once we have detected the point between the eyes, it is fairly easy to locate the eyes, which are the two small darkest parts on each side of this point. Because detecting a point between the eyes is easier and more stable than detecting the eyes directly, the system can track the eyes robustly. We implemented the system on an SGI O2 workstation. The video image size is 320×240 pixels. The system processes images at seven frames per second in the detection mode and at 13 frames per second in the tracking mode, without any special hardware