Eye Localization based on Multi-Scale Gabor Feature Vector Model

• DOI: 10.5392/jkca.2007.7.1.048
• Publication Date: 2012-08-20T07:10:44Z
• Authors: Sang-Hoon Kim; Sou-Hwan Jung; Du-Sik Oh; Jae-Min Kim; Seong-Won Cho; Sun-Tae Chung
• Keywords: 0508 media and communications; 0502 economics and business; 05 social sciences

Eye localization is necessary for face recognition and related application areas. Most of eye localization algorithms reported thus far still need to be improved about precision and computational time for successful applications. In this paper, we propose an improved eye localization method based on multi-scale Gator feature vector models. The proposed method first tries to locate eyes in the downscaled face image by utilizing Gabor Jet similarity between Gabor feature vector at an initial eye coordinates and the eye model bunch of the corresponding scale. The proposed method finally locates eyes in the original input face image after it processes in the same way recursively in each scaled face image by using the eye coordinates localized in the downscaled image as initial eye coordinates. Experiments verify that our proposed method improves the precision rate without causing much computational overhead compared with other eye localization methods reported in the previous researches.