Dimensionality reduction of multi-scale feature spaces using a separability criterion.
Kamran EtemadRamalingam ChellappaPublished in: ICASSP (1995)
Keyphrases
- dimensionality reduction
- multiscale
- class separability
- feature space
- feature selection
- high dimensional
- high dimensionality
- principal component analysis
- low dimensional
- data points
- high dimensional data
- input space
- pattern recognition
- image representation
- linear discriminant analysis
- data representation
- random projections
- feature extraction
- scale space
- dimensionality reduction methods
- linear dimensionality reduction
- wavelet transform
- principal components
- coarse to fine
- manifold learning
- pattern recognition and machine learning
- edge detection
- lower dimensional
- multiple scales
- image processing
- natural images
- metric learning
- singular value decomposition
- kernel pca
- sparse representation
- graph embedding
- feature vectors
- face recognition