93 search results - page 2 / 19 » Greedy Kernel Principal Component Analysis |
ICPR
2006
IEEE
2006
IEEE
Regularized Locality Preserving Learning of Pre-Image Problem in Kernel Principal Component Analysis
13 years 11 months ago
In this paper, we address the pre-image problem in kernel principal component analysis (KPCA). The preimage problem finds a pattern as the pre-image of a feature vector defined in...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
NIPS
2008
13 years 6 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
ICIP
2005
IEEE
13 years 10 months ago
2005
IEEE
This paper presents a view independent face recognition method based on kernel principal component analysis (KPCA) of local parts. View changes induce large variation in feature s...
PR
2006
2006
Correspondence matching using kernel principal components analysis and label consistency constraints
13 years 5 months ago
This paper investigates spectral approaches to the problem of point pattern matching. We make two contributions. First, we consider rigid point-set alignment. Here we show how ker...