Feature Space Reduction for Face Recognition with Dual Linear Discriminant Analysis.
Krzysztof KucharskiWladyslaw SkarbekMiroslaw BoberPublished in: CAIP (2005)
Keyphrases
- linear discriminant analysis
- face recognition
- feature space
- discriminant analysis
- principal component analysis
- dimensionality reduction
- feature extraction
- discriminant features
- dimension reduction
- small sample size
- generalized discriminant analysis
- high dimensional data
- recognition rate
- subspace methods
- null space
- face images
- support vector machine svm
- face detection
- class separability
- feature selection
- input space
- scatter matrix
- support vector
- feature analysis
- training samples
- fisher criterion
- kernel discriminant analysis
- linear discriminant
- high dimensional feature space
- gabor features
- nonparametric discriminant analysis
- high dimensionality
- human faces
- high dimensional
- sparse representation
- input data
- dimensionality reduction methods
- data points
- facial expressions
- subspace analysis
- neural network
- machine learning
- discriminant vectors
- qr decomposition
- discriminant information
- feature set
- scatter matrices
- kernel trick
- locality preserving projections
- face verification
- gabor wavelets
- kernel pca