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Eye-Tracking Algorithm for Low Webcam Image Resolution Without Calibration

Applications of eye-tracking devices aim to understand human activities and behaviors, improve human interactions with robots, and develop assistive technology in helping people with some communication disabilities. This paper proposes an algorithm to detect the pupil center and user’s gaze direction in real-time, using a low-resolution webcam and a conventional computer with no need for calibration. Given the constraints, the gaze space was reduced to five states: left, right, center, up, and eyes closed. A pre-existing landmarks detector was used to identify the user’s eyes. We employ image processing techniques to find the center of the pupil and we use the coordinates of the points found associated with mathematical calculations to classify the gaze direction. By using this method, the algorithm achieved 81.9% overall accuracy results even under variable and non-uniform environmental conditions. We also performed quantitative experiments with noise, blur, illumination, and rotation variation. Smart Eye Communicator, the proposed algorithm, can be used as eye-tracking mechanism to help people with communication difficulties to express their desires.