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Construction of Composite Feature Vector Based on Discriminant Analysis for Face Recognition
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 Title & Authors
Construction of Composite Feature Vector Based on Discriminant Analysis for Face Recognition
Choi, Sang-Il;
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 Abstract
We propose a method to construct composite feature vector based on discriminant analysis for face recognition. For this, we first extract the holistic- and local-features from whole face images and local images, which consist of the discriminant pixels, by using a discriminant feature extraction method. In order to utilize both advantages of holistic- and local-features, we evaluate the amount of the discriminative information in each feature and then construct a composite feature vector with only the features that contain a large amount of discriminative information. The experimental results for the FERET, CMU-PIE and Yale B databases show that the proposed composite feature vector has improvement of face recognition performance.
 Keywords
Holistic-feature;Local-feature;Feature Selection;Face Recognition;Discriminant Analysis;
 Language
Korean
 Cited by
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