| 한글제목(Korean Title) |
Global Feature Extraction and Recognition from Matrices of Gabor Feature Faces |
| 영문제목(English Title) |
Global Feature Extraction and Recognition from Matrices of Gabor Feature Faces |
| 저자(Author) |
Wilfred O. Odoyo
Beom-Joon Cho
|
| 원문수록처(Citation) |
VOL 09 NO. 02 PP. 0207 ~ 0211 (2011. 04) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
This paper presents a method for facial feature representation and recognition from the Covariance Matrices of the Gabor-filtered images. Gabor filters are a very powerful tool for processing images that respond to different local orientations and wave numbers around points of interest, especially on the local features on the face. This is a very unique attribute needed to extract special features around the facial components like eyebrows, eyes, mouth and nose. The Covariance matrices computed on Gabor filtered faces are adopted as the feature representation for face recognition. Geodesic distance measure is used as a matching measure and is preferred for its global consistency over other methods. Geodesic measure takes into consideration the position of the data points in addition to the geometric structure of given face images. The proposed method is invariant and robust under rotation, pose, or boundary distortion. Tests run on random images and also on publicly available JAFFE and FRAV3D face recognition databases provide impressively high percentage of recognition. |
| 키워드(Keyword) |
covariance matrices
gabor filters (kernels)
eigenvectors
facial component features
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| 파일첨부 |
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