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CVPR
2008
IEEE
14 years 9 months ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
ICIP
2005
IEEE
14 years 1 months ago
View independent face recognition based on kernel principal component analysis of local parts
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...
Koji Hotta
PR
2006
116views more  PR 2006»
13 years 7 months ago
Correspondence matching using kernel principal components analysis and label consistency constraints
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...
Hongfang Wang, Edwin R. Hancock
GPB
2010
231views Solid Modeling» more  GPB 2010»
13 years 4 months ago
Mining Gene Expression Profiles: An Integrated Implementation of Kernel Principal Component Analysis and Singular Value Decompos
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
Ferran Reverter, Esteban Vegas, Pedro Sánch...
DAGSTUHL
2006
13 years 9 months ago
Greedy Kernel Principal Component Analysis
Vojtech Franc, Václav Hlavác