Facial feature extraction using PCA and wavelet multi-resolution images

Authors:
Kyung-A Kim;Se-Young Oh;Hyun-Chul Choi
Affiliations:
Dept. of Electrical Eng., Pohang University of Science and Technology, Pohang, Kyungbuk, South Korea;Dept. of Electrical Eng., Pohang University of Science and Technology, Pohang, Kyungbuk, South Korea;Dept. of Electrical Eng., Pohang University of Science and Technology, Pohang, Kyungbuk, South Korea
Venue:
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Year:
2004

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Abstract

This paper presents a novel algorithm for the extraction of the facial feature (eyebrow, eye, nose and mouth) fields from 2-D gray-level face images. The fundamental philosophy is that eigenfeatures, derived from the eigenvalues and eigenvectors of the gray-level data set constructed from the feature fields, are very useful to locate these fields efficiently. In addition, multi-resolution images, derived from a 2-D DWT (Discrete Wavelet Transform), are used to save the search time of the facial features. The experimental results indicate that the proposed algorithm is robust against facial feature size and slight variations of pose.