A comparative study of feature extraction using PCA and LDA for face recognition.
Erwin HidayatNur A. FajrianAzah Kamilah MudaYun-Huoy ChooSabrina AhmadPublished in: IAS (2011)
Keyphrases
- face recognition
- feature extraction
- linear discriminant analysis
- principal component analysis
- discriminant analysis
- pca lda
- principal components analysis
- principle component analysis
- face images
- gabor features
- dimension reduction
- face databases
- dimensionality reduction
- recognition rate
- subspace methods
- recognition accuracy
- local binary pattern
- face detection
- human faces
- small sample size
- feature vectors
- kernel principal component analysis
- linear discriminate analysis
- computer vision
- orl face
- discriminant information
- pattern recognition
- feature space
- support vector machine svm
- method for face recognition
- independent component analysis
- principal components
- feature representation
- gabor wavelets
- kernel pca
- facial images
- image classification
- appearance based face recognition
- facial expressions
- scatter matrix
- facial expression recognition
- singular value decomposition
- sparse representation
- texture analysis
- manifold learning
- generalized discriminant analysis
- support vector machine
- discriminant projection
- recognizing faces
- fisher linear discriminant
- subspace analysis
- covariance matrix
- face verification