TWO-Dimensional Linear Discriminant Analysis of Principle Component Vectors for Face Recognition.
Parinya SanguansatWidhyakorn AsdornwisedSomchai JitapunkulSanparith MarukatatPublished in: ICASSP (2) (2006)
Keyphrases
- linear discriminant analysis
- face recognition
- discriminant analysis
- principal component analysis
- discriminant vectors
- small sample size
- dimensionality reduction
- discriminant information
- feature extraction
- discriminant features
- dimension reduction
- null space
- high dimensional data
- feature space
- face images
- principal components
- support vector
- subspace methods
- vector space
- fisher criterion
- feature vectors
- discriminative information
- support vector machine svm
- generalized discriminant analysis
- recognition rate
- feature analysis
- facial expressions
- linear discriminant
- computer vision
- scatter matrix
- kernel pca
- locality preserving projections
- kernel discriminant analysis
- pca lda
- qr decomposition
- data analysis
- nonparametric discriminant analysis
- high dimensional
- subspace analysis
- gabor wavelets
- subspace learning
- facial images
- recognition accuracy
- high dimensionality
- sparse representation