PCA versus LDA.
Aleix M. MartínezAvinash C. KakPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2001)
Keyphrases
- linear subspace
- face recognition
- subspace methods
- principal component analysis
- linear discriminant analysis
- low dimensional
- subspace analysis
- subspace learning
- dimensionality reduction
- discriminant analysis
- latent dirichlet allocation
- feature extraction
- dimension reduction
- high dimensional data
- linear discriminate analysis
- recognition rate
- face images
- high dimensional
- gabor features
- facial expressions
- principle component analysis
- face databases
- feature space
- topic modeling
- topic models
- small sample size
- principal components
- pca lda
- principal components analysis
- scatter matrices
- orl face
- lower dimensional
- independent component analysis
- computer vision
- machine learning
- kernel pca
- latent semantic analysis
- kernel principal component analysis
- covariance matrix
- discriminating power
- co occurrence
- support vector
- discriminant information
- classical linear discriminant analysis
- data sets