A closed-form unsupervised geometry-aware dimensionality reduction method in the Riemannian Manifold of SPD matrices.
Marco CongedoPedro Luiz Coelho RodriguesFlorent BouchardAlexandre BarachantChristian JuttenPublished in: EMBC (2017)
Keyphrases
- closed form
- spd matrices
- riemannian manifolds
- symmetric positive definite
- geometric structure
- dimensionality reduction
- lie group
- geodesic distance
- euclidean space
- positive definite
- diffusion tensor
- gaussian mixture
- rigid motion
- log euclidean
- distribution function
- point correspondences
- manifold learning
- mean shift
- semi supervised
- feature space
- principal component analysis
- data sets
- covariance matrices
- vector space
- euclidean distance
- machine learning
- linear discriminant analysis
- maximum likelihood
- low dimensional
- feature extraction
- input space
- metric space
- dimension reduction
- infinite dimensional
- high dimensional