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» A Framework of 2D Fisher Discriminant Analysis: Application ...
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ECCV
2006
Springer
9 years 11 months ago
Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
Guang Dai, Dit-Yan Yeung, Hong Chang
TIP
2008
287views more  TIP 2008»
8 years 9 months ago
3-D Object Recognition Using 2-D Views
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize...
Wenjing Li, George Bebis, Nikolaos G. Bourbakis
SIBGRAPI
2005
IEEE
9 years 2 months ago
A Maximum Uncertainty LDA-Based Approach for Limited Sample Size Problems : With Application to Face Recognition
A critical issue of applying Linear Discriminant Analysis (LDA) is both the singularity and instability of the within-class scatter matrix. In practice, particularly in image recog...
Carlos E. Thomaz, Duncan Fyfe Gillies
CVPR
2008
IEEE
8 years 9 months ago
Robust learning of discriminative projection for multicategory classification on the Stiefel manifold
Learning a robust projection with a small number of training samples is still a challenging problem in face recognition, especially when the unseen faces have extreme variation in...
Duc-Son Pham, Svetha Venkatesh
AUSAI
2005
Springer
9 years 2 months ago
Resampling LDA/QR and PCA+LDA for Face Recognition
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...
Jun Liu, Songcan Chen
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