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http://dx.doi.org/10.9717/kmms.2012.15.6.722

Comparative Performance Evaluations of Eye Detection algorithm  

Gwon, Su-Yeong (동국대학교 전자전기공학부)
Cho, Chul-Woo (동국대학교 전자전기공학부)
Lee, Won-Oh (동국대학교 전자전기공학부)
Lee, Hyeon-Chang (동국대학교 전자공학과)
Park, Kang-Ryoung (동국대학교 전자전기공학부)
Lee, Hee-Kyung (한국전자통신연구원)
Cha, Ji-Hun (한국전자통신연구원)
Publication Information
Journal of Korea Multimedia Society / v.15, no.6, 2012 , pp. 722-730 More about this Journal
Abstract
Recently, eye image information has been widely used for iris recognition or gaze detection in biometrics or human computer interaction. According as long distance camera-based system is increasing for user's convenience, the noises such as eyebrow, forehead and skin areas which can degrade the accuracy of eye detection are included in the captured image. And fast processing speed is also required in this system in addition to the high accuracy of eye detection. So, we compared the most widely used algorithms for eye detection such as AdaBoost eye detection algorithm, adaptive template matching+AdaBoost algorithm, CAMShift+AdaBoost algorithm and rapid eye detection method. And these methods were compared with images including light changes, naive eye and the cases wearing contact lens or eyeglasses in terms of accuracy and processing speed.
Keywords
AdaBoost; CAMShift; Rapid Eye Detection; Adaptive Template Matching; Eye Detection;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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