Two-Dimensional Linear Discriminant Analysis of Principle Component Vectors for Face Recognition.
Parinya SanguansatWidhyakorn AsdornwisedSomchai JitapunkulSanparith MarukatatPublished in: IEICE Trans. Inf. Syst. (2006)
Keyphrases
- linear discriminant analysis
- face recognition
- discriminant analysis
- discriminant vectors
- small sample size
- dimensionality reduction
- principal component analysis
- dimension reduction
- discriminant information
- discriminant features
- feature extraction
- recognition rate
- subspace methods
- support vector machine svm
- feature space
- face images
- null space
- fisher criterion
- support vector
- high dimensional data
- face detection
- principal components
- nonparametric discriminant analysis
- facial images
- gabor features
- recognition accuracy
- scatter matrix
- lower dimensional
- kernel discriminant analysis
- locality preserving projections
- feature vectors
- scatter matrices
- linear discriminant
- vector space
- nearest neighbor
- discriminative information
- human faces
- multi class
- support vector machine
- sparse representation
- gabor wavelets
- high dimensional
- computer vision
- generalized discriminant analysis
- data sets