An uncorrelated fisherface approach
Jing X.-Y.4; Wong H.-S.2; Zhang D.1; Tang Y.-Y.3
Source PublicationNeurocomputing
Volume67Issue:1-4 SUPPL.Pages:328-334
AbstractThe Fisherface method is the most representative method of the linear discrimination analysis (LDA) technique. However, there persists in the Fisherface method at least two areas of weakness. The first weakness is that it cannot make the achieved discrimination vectors completely satisfy the statistical uncorrelation while costing a minimum of computing time. The second weakness is that not all the discrimination vectors are useful in pattern classification. In this paper, we propose an uncorrelated Fisherface approach (UFA) to improve the Fisherface method in these two areas. Experimental results on different image databases demonstrate that UFA outperforms the Fisherface method and the uncorrelated optimal discrimination vectors (UODV) method. © 2005 Elsevier B.V. All rights reserved.
KeywordComputing time Discrimination vectors selection Linear discrimination analysis (LDA) Statistical uncorrelation Uncorrelated Fisherface approach (UFA)
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Cited Times [WOS]:5   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Hong Kong Polytechnic University
2.City University of Hong Kong
3.Hong Kong Baptist University
4.Harbin Institute of Technology
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Jing X.-Y.,Wong H.-S.,Zhang D.,et al. An uncorrelated fisherface approach[J]. Neurocomputing,2005,67(1-4 SUPPL.):328-334.
APA Jing X.-Y.,Wong H.-S.,Zhang D.,&Tang Y.-Y..(2005).An uncorrelated fisherface approach.Neurocomputing,67(1-4 SUPPL.),328-334.
MLA Jing X.-Y.,et al."An uncorrelated fisherface approach".Neurocomputing 67.1-4 SUPPL.(2005):328-334.
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