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  • 标题:Eye Detection and Tracking in Image with Complex Background
  • 本地全文:下载
  • 作者:Mohammadali Azimi Kashani ; Mahdi Mollaei Arani ; Mohammad Reza Ramezanpour
  • 期刊名称:Journal of Emerging Trends in Computing and Information Sciences
  • 电子版ISSN:2079-8407
  • 出版年度:2011
  • 卷号:2
  • 期号:4
  • 页码:182-186
  • 出版社:ARPN Publishers
  • 摘要: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 our next steps. We 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 we will obtain the pupil position. In the next step, we perform eye tracking. In the proposed method, eye detection and tracking are applied on testing sets, gathered from different images of face data with complex backgrounds. Experiments indicate correct detection rate of 94.9%, which is indicative of the method’s superiority and high robustness.
  • 关键词:eye detection; eye tracking; kallman filter
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