A two-stage linear discriminant analysis for face recognition
Author(s)
Sharma, Alok
Paliwal, Kuldip K
Griffith University Author(s)
Year published
2012
Metadata
Show full item recordAbstract
A two-stage linear discriminant analysis technique is proposed that utilizes both the null space and range space information of scatter matrices. The technique regularizes both the between-class scatter and within-class scatter matrices to extract the discriminant information. The regularization is conducted in parallel to give two orientation matrices. These orientation matrices are concatenated to form the final orientation matrix. The proposed technique is shown to provide better classification performance on face recognition datasets than the other techniques.A two-stage linear discriminant analysis technique is proposed that utilizes both the null space and range space information of scatter matrices. The technique regularizes both the between-class scatter and within-class scatter matrices to extract the discriminant information. The regularization is conducted in parallel to give two orientation matrices. These orientation matrices are concatenated to form the final orientation matrix. The proposed technique is shown to provide better classification performance on face recognition datasets than the other techniques.
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Journal Title
Pattern Recognition Letters
Volume
33
Issue
9
Subject
Cognitive and computational psychology