Dimensionality Reduction for Semi-supervised Face Recognition.
Weiwei DuKohei InoueKiichi UrahamaPublished in: FSKD (2) (2005)
Keyphrases
- dimensionality reduction
- subspace learning
- semi supervised
- face recognition
- linear discriminant analysis
- principal component analysis
- semi supervised dimensionality reduction
- linear dimensionality reduction
- feature extraction
- neighborhood preserving
- low dimensional
- manifold learning
- high dimensional
- sparse representation
- high dimensional data
- label information
- high dimensionality
- data representation
- discriminant analysis
- unsupervised learning
- metric learning
- neighborhood preserving embedding
- labeled data
- semi supervised learning
- locality preserving projections
- dimensionality reduction methods
- pattern recognition
- recognition rate
- graph embedding
- kernel pca
- face images
- data points
- pairwise
- multi view
- kernel learning
- feature selection
- lower dimensional
- feature space
- pattern recognition and machine learning
- structure preserving
- dimension reduction
- random projections
- kernel discriminant analysis
- principal components
- human faces
- active learning
- nonlinear dimensionality reduction
- co training
- semi supervised clustering
- facial images
- semi supervised classification
- local binary pattern
- unlabeled data
- face databases
- pairwise constraints
- support vector
- computer vision
- face detection
- data sets
- learning algorithm
- neural network