Geodesic Discriminant Analysis for Manifold-Valued Data.
Maxime LouisBenjamin CharlierStanley DurrlemanPublished in: CVPR Workshops (2018)
Keyphrases
- discriminant analysis
- valued data
- riemannian metric
- tensor field
- covariance matrices
- geodesic distance
- graph embedding
- linear discriminant analysis
- covariance matrix
- principal component analysis
- shape space
- face recognition
- log euclidean
- order statistics
- maximum likelihood
- euclidean space
- feature extraction
- gaussian mixture model
- affine invariant
- manifold learning
- vector space
- feature space
- mixture model
- euclidean distance
- riemannian manifolds
- low dimensional
- structure tensor
- gaussian distribution
- white matter
- fisher information
- high dimensional
- gaussian mixture
- shape analysis
- nearest neighbor
- machine learning