Keyphrases
- kernel pca
- principal component analysis
- kernel principal component analysis
- principal components analysis
- principal components
- feature extraction
- dimensionality reduction
- principle component analysis
- linear dimensionality reduction
- face recognition
- linear discriminant analysis
- covariance matrix
- signal processing
- dimension reduction
- high dimensional feature space
- feature space
- gabor features
- subspace methods
- face representation and recognition
- highly nonlinear
- nonlinear equations
- data sets
- subspace learning
- random projections
- negative matrix factorization
- kernel methods
- singular value decomposition
- sufficient conditions
- low dimensional
- k means
- high dimensional
- pattern recognition
- image sequences
- computer vision