Keyphrases
- dimensionality reduction
- low dimensional
- manifold learning
- high dimensional data
- high dimensional
- principal component analysis
- pattern recognition
- feature extraction
- image registration
- motion analysis
- feature selection
- random projections
- input space
- linear discriminant analysis
- data representation
- dimensionality reduction methods
- metric learning
- neural network
- euclidean distance
- data points
- nonlinear dimensionality reduction
- high dimensionality
- feature space
- low dimensional spaces
- principal components
- unsupervised feature selection
- supervised dimensionality reduction
- nonrigid shape
- singular value decomposition
- high dimensional spaces
- kernel pca
- motion tracking
- locally linear embedding
- deformable shapes
- feature points
- linear projection
- nearest neighbor
- face recognition
- computer vision