15 search results - page 2 / 3 » A Framework of 2D Fisher Discriminant Analysis: Application ... |
ECCV
2006
Springer
14 years 6 months ago
2006
Springer
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...
TIP
2008
13 years 4 months ago
2008
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...
SIBGRAPI
2005
IEEE
13 years 10 months ago
2005
IEEE
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...
CVPR
2008
IEEE
13 years 4 months ago
2008
IEEE
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...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
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...