A invertible dimension reduction of curves on a manifold.
Sheng YiHamid KrimLarry K. NorrisPublished in: ICCV Workshops (2011)
Keyphrases
- dimension reduction
- manifold learning
- low dimensional
- manifold embedding
- high dimensional
- nonlinear manifold
- principal component analysis
- manifold learning algorithm
- generative topographic mapping
- feature space
- feature extraction
- dimensionality reduction
- intrinsic dimension
- high dimensional problems
- discriminative information
- high dimensional data
- linear discriminant analysis
- singular value decomposition
- manifold structure
- shape space
- high dimensionality
- feature selection
- random projections
- locally linear embedding
- diffusion maps
- high dimensional data analysis
- cluster analysis
- geodesic distance
- riemannian manifolds
- linear subspace
- head pose estimation
- unsupervised learning
- data points
- dimension reduction methods
- euclidean space
- model selection
- preprocessing
- training data