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With the rapid development of human-computer interaction systems, eye tracking algorithm has become a very popular research field. As the most important part in eye tracking, pupil positioning algorithm is still facing many challenges, especially in processing non-ideal eye images. In this paper we propose an accurate and robust pupil positioning algorithm using Adaboost cascade detector and improved starburst model. Firstly, we use an average linear interpolating method to interpolate the specular reflections. Secondly, we combine HAAR features and Adaboost cascade detector to extract the region of interest (ROI) from the eye image (after specular reflections removal). Lastly, the improved starburst model is adopted to locate the pupil contour and the pupil center. In order to evaluate the performance of proposed method, we collect several eye moving videos using the specified camera device and the experimental results prove that the accuracy and robustness of proposed algorithm are better.

Accurate and Robust Pupil Positioning Algorithm Using Adaboost Cascade Detector and Improved Starburst Model