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http://dx.doi.org/10.9717/kmms.2015.18.9.1039

Feature Generation Method for Low-Resolution 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.9, 2015 , pp. 1039-1046 More about this Journal
Abstract
We propose a feature generation method for low-resolution face recognition. For this, we first generate new features from the input features (pixels) of a low-resolution face image by adding the higher-order terms. Then, we evaluate the separability of both of the original input features and new features by computing the discriminant distance of each feature. Finally, new data sample used for recognition consists of the features with high separability. The experimental results for the FERET, CMU-PIE and Yale B databases show that the proposed method gives good recognition performance for low-resolution face images compared with other method.
Keywords
Feature Generation; Feature Selection; Discriminant Distance; Low-resolution Face Recognition;
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