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http://dx.doi.org/10.9717/kmms.2015.18.7.834

Construction of Composite Feature Vector Based on Discriminant Analysis for Face Recognition  

Choi, Sang-Il (Dept. of Computer Science and Engineering, Graduate School, Dankook University)
Publication Information
Journal of Korea Multimedia Society / v.18, no.7, 2015 , pp. 834-842 More about this Journal
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;
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Times Cited By KSCI : 1  (Citation Analysis)
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