Kernel Relative Principal Component Analysis for Pattern Recognition.
Yoshikazu WashizawaKenji HikidaToshihisa TanakaYukihiko YamashitaPublished in: SSPR/SPR (2004)
Keyphrases
- pattern recognition
- principal component analysis
- dimensionality reduction
- kernel pca
- feature space
- feature extraction
- principal components
- kernel function
- covariance matrix
- pattern recognition problems
- kernel methods
- kernel principal component analysis
- positive definite
- image analysis
- neural network
- support vector machine svm
- image processing
- low dimensional
- face images
- input space
- independent component analysis
- dimension reduction
- pattern analysis
- discriminant analysis
- lower dimensional
- kernel space
- linear discriminant analysis
- signal processing
- computer vision
- machine learning
- pattern classification
- singular value decomposition
- negative matrix factorization
- kernel matrix
- support vector
- face recognition
- graph matching
- high dimensional data
- similarity measure