NDLI: Eye detection and tracking in image with complex background

Content Provider	IEEE Xplore Digital Library
Author	Fini, M.R.R. Kashani, M.A.A. Rahmati, M.
Copyright Year	2011
Description	Author affiliation: Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran (Rahmati, M.) \|\| Department of Computer Science & Research Branch, Islamic Azad University Branch shoushtar, Kashan, Iran (Fini, M.R.R.; Kashani, M.A.A.)
Abstract	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 horizontal projection obtained 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 candidate's. 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 method's superiority and high robustness.
Starting Page	57
Ending Page	61
File Size	490807
Page Count	5
File Format	PDF
ISBN	9781424486786
e-ISBN	9781424486793
DOI	10.1109/ICECTECH.2011.5942050
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-08
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image color analysis eye tracking Feature extraction Skin Mathematical model Face Equations Pixel kallman filter eye detection
Content Type	Text
Resource Type	Article

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