Feature Selection Based on KPCA, SVM and GSFS for Face Recognition.
Weihong LiWeiguo GongYixiong LiangWeimin ChenPublished in: ICAPR (2) (2005)
Keyphrases
- face recognition
- feature selection
- support vector
- linear discriminant analysis
- kernel principal component analysis
- feature extraction
- support vector machine
- feature space
- support vector machine svm
- face images
- discriminant analysis
- subspace methods
- text categorization
- kernel pca
- multi class
- selected features
- local binary pattern
- kernel function
- dimensionality reduction
- knn
- recognition rate
- text classification
- face databases
- human faces
- mutual information
- classification accuracy
- bayes classifier
- feature reduction
- machine learning
- input features
- feature ranking
- svm rfe
- kernel methods
- facial expressions
- small sample
- feature selection algorithms
- web image annotation
- feature subset
- feature set
- principal component analysis
- preprocessing
- classification performances
- facial images
- linear svm
- model selection
- text classifiers
- svm classifier
- k nearest neighbor
- subspace learning
- kernel matrix
- multi task
- principal components
- face detection
- high dimensional feature space
- high dimensional
- pattern recognition
- similarity measure
- computer vision