206 search results - page 1 / 42 » PCA in Autocorrelation Space |
ICPR
2002
IEEE
14 years 5 months ago
2002
IEEE
The use of higher order autocorrelations as features for pattern classification has been usually restricted to second or third orders due to high computational costs. Since the au...
TIP
2011
12 years 11 months ago
2011
—This paper introduces kernel versions of maximum autocorrelation factor (MAF) analysis and minimum noise fraction (MNF) analysis. The kernel versions are based upon a dual formu...
PAMI
2008
13 years 4 months ago
2008
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...
CSDA
2010
13 years 4 months ago
2010
Kernel Principal Component Analysis extends linear PCA from a Euclidean space to any reproducing kernel Hilbert space. Robustness issues for Kernel PCA are studied. The sensitivit...
ACII
2005
Springer
13 years 10 months ago
2005
Springer
This paper proposes a new facial expression recognition method which combines Higher Order Local Autocorrelation (HLAC) features with Weighted PCA. HLAC features are computed at ea...