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Linear discriminant relationship analysis between all classes and class specified for face recognition
Wu X.3; Tang Y.Y.1; Fang B.3; Shang Z.3; Xing C.3
2013
Source PublicationInternational Journal of Applied Mathematics and Statistics
ISSN09737545 09731377
Volume51Issue:23Pages:384-392
AbstractClass specified-based feature extraction method becomes an important reference in classification, such as common vector(CV) algorithm and class frequency analysis(CFA). CV algorithm does not consider the relationship among the different classes, but CFA does while only works on the frequency domain. Furthermore, we found that the relationship among different classes is also important in recognition task. To overcome the disadvantages mentioned above, we proposed an algorithm to adjust the relationship among subspaces of different classes, and at last achieved smaller within-class scatter in each class, larger between-class scatter and closer mean centers in the remaining classes. In the case, features of each class and the relationship with the remaining classes can be shown clearly in its the whole feature subspace. Moreover, it relieves the restriction in a same subspace. We also study the comparable problem in multiple subspaces and reorganize different subspaces in our objective function. The proposed algorithm is an important supplement to CFA and CV in linear discriminant relationship analysis. The experimental results show its advantages in orl and Extend yale B face database. Furthermore, the proposed method is not limited to face recognition, also can be extended to other image-based object recognition. © 2013 by CESER Publications.
KeywordCFA Class dependence Common vector LDA
URLView the original
Language英語English
Fulltext Access
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Universidade de Macau
2.Yangtze Normal University
3.Chongqing University
Recommended Citation
GB/T 7714
Wu X.,Tang Y.Y.,Fang B.,et al. Linear discriminant relationship analysis between all classes and class specified for face recognition[J]. International Journal of Applied Mathematics and Statistics, 2013, 51(23), 384-392.
APA Wu X.., Tang Y.Y.., Fang B.., Shang Z.., & Xing C. (2013). Linear discriminant relationship analysis between all classes and class specified for face recognition. International Journal of Applied Mathematics and Statistics, 51(23), 384-392.
MLA Wu X.,et al."Linear discriminant relationship analysis between all classes and class specified for face recognition".International Journal of Applied Mathematics and Statistics 51.23(2013):384-392.
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