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Eye Detection Using Texture Filters  

Park, Chan-Woo (Dept. of Comp. Sci. and Eng., Hanyang University)
Kim, Yong-Min (Dept. of Comp. Sci. and Eng., Hanyang University)
Park, Ki-Tae (Ambient Intelligence Software Team, Institute of Hanyang BK21, Hanyang University)
Moon, Young-Shik (Dept. of Comp. Sci. and Eng., Hanyang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.46, no.6, 2009 , pp. 70-78 More about this Journal
Abstract
In this paper, we propose a novel method for eye detection using two texture filters considering textural and structural characteristics of eye regions. The human eyes have two characteristics: 1) the eyes are horizontally long and 2) the pupas are of circular shapes. By considering these two characteristics of human eyes, two texture filters are utilized for the eye detection. One is Gabor filter for detecting eye shapes in horizontal direction. The other is ART descriptor for detecting pupils of circular shape. In order to effectively detect eye regions, the proposed method consists of four steps. The first step is to extract facial regions using AdaBoost method. The second step is to normalize the illumination by considering local information. The third step is to estimate candidate regions for eyes, by merging the results from two texture filters. The final step is to locate exact eye regions by using geometric information of the face. As experimental results, the performance of the proposed method has been improved by 2.9~4.4%, compared to the existing methods.
Keywords
Eye Detection; Gabor Filter; ART;
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Times Cited By KSCI : 1  (Citation Analysis)
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