The ability to automatically detect eye center locations in video images allows for estimating gaze direction. This, in turn, facilitates the study of human-computer interaction and behavioral analyses of social interactions. We propose an improved eye center localization method based on the Hough transform, called Circle-based Eye Center Localization (CECL) that is simple, robust, and achieves accuracy at a par with typically more complex state-of-the-art methods. The CECL method relies on color and shape cues that distinguish the iris from other facial structures.
The circle enclosing the iris is localized by means of the Hough transform and the center of the iris is determined using the intensity level within the detected circle. The accuracy of the CECL method is demonstrated through a comparison with 15 state-of-the-art eye center localization methods against five error thresholds, as reported in the literature. The CECL method achieved an accuracy of 80.8% to 99.4% and ranked first for 2 of the 5 thresholds. It is concluded that the CECL method offers an attractive alternative to existing methods for automatic eye center localization.