Fast Kernel Generalized Discriminative Common Vectors for Feature Extraction.
Katerine Díaz-ChitoJesús Martínez del RincónAura Hernández-SabatéMarçal RusiñolFrancesc J. FerriPublished in: J. Math. Imaging Vis. (2018)
Keyphrases
- feature extraction
- feature vectors
- feature space
- kernel principal component analysis
- dot product
- kernel function
- image classification
- discriminant analysis
- dimensionality reduction
- feature selection
- high dimensional feature space
- wavelet transform
- preprocessing
- image processing
- fisher kernel
- kernel pca
- dimension reduction
- discriminant information
- principal components
- linear discriminant analysis
- kernel methods
- face recognition
- frequency domain
- support vector machine svm
- texture classification
- class separability
- principal component analysis
- linear feature extraction
- pattern classification
- support vector
- input space
- high dimensional
- feature representation
- feature set
- discriminative power
- spatial pyramid
- principle component analysis
- input data
- reproducing kernel hilbert space
- vector space
- extracted features
- maximum likelihood
- texture analysis
- neural network