Eye detection and tracking in images with using bag of pixels
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 using mixture of Gaussian, this will cause the images background to be non effective in our next steps. We used the bag of pixels technique from face region, to separate a region containing eyes and eyebrow. This will result in decreasing the computational complexity and ignoring some factors such as bread. Finally, in proposed method points with the highest values of are selected as the eye candidates. The eye region is well detected among these points. Color entropy in the eye region is used to eliminate the irrelevant candidates. 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 methods superiority and high robustness.
eye detection eye tracking kallman filter bag of pixels
Mohammad Ali Azimi Kashani Mahdi Mollaei Arani Mohammad Reza Ramezanpour Fini
Department of Computer Science & Research Branch Islamic Azad University Branch Shoushtar Shoushtar, Department of Computer Science & Research Branch Payame Noor University Ardestan, Iran Department of Computer Science & Research Branch Islamic Azad University Branch Kashan Kashan, Iran
国际会议
西安
英文
64-68
2011-05-13（万方平台首次上网日期，不代表论文的发表时间）