Open AccessComposite vector selection for feature extraction in face recognition
Author(s) -
Choi SangIl,
Choi Younggeun,
Kim Hyunjin
Publication year - 2013
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2012.3416
Subject(s) - composite number , pattern recognition (psychology) , artificial intelligence , facial recognition system , discriminant , linear discriminant analysis , feature selection , computer science , selection (genetic algorithm) , feature extraction , feature vector , face (sociological concept) , support vector machine , algorithm , social science , sociology
Proposed is a composite vector selection method based on discriminant analysis for face recognition. By measuring the amount of discriminant information in each composite vector, informative composite vectors can be selected. Then, composite features for face recognition are extracted with only the selected composite vectors. The experimental results show that the proposed method results in improved performance.