48 search results - page 9 / 10 » Random Sampling LDA for Face Recognition |
ICCV
2007
IEEE
14 years 6 months ago
2007
IEEE
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
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...
ICPR
2008
IEEE
13 years 11 months ago
2008
IEEE
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
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...
FGR
2004
IEEE
13 years 8 months ago
2004
IEEE
Data collection for both training and testing a classifier is a tedious but essential step towards face detection and recognition. All of the statistical methods suffer from this ...