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To detect and track eye images with complex background, distinctive features of user eye are used. Generally, an eye-tracking and detection system can be divided into four steps: face detection, eye region detection, pupil detection and eye tracking. To find the position of pupil, first, face region must be separated from the rest of the image, this will cause the images background to be non effective in the authors' next steps. They used the horizontal projection obtained from face region, to separate a region of face containing eyes and eyebrow. This will result in decreasing the computational complexity and ignoring some factors such as bread. Finally, by proposed algorithm they will obtain the pupil position. In the next step, they perform eye tracking.
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