Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds.
Ming YinYi GuoJunbin GaoZhaoshui HeShengli XiePublished in: CVPR (2016)
Keyphrases
- subspace clustering
- riemannian manifolds
- high dimensional
- symmetric positive definite
- positive definite
- high dimensional data
- kernel function
- euclidean space
- low dimensional
- feature space
- manifold learning
- kernel matrix
- clustering method
- geometric structure
- subspace clusters
- high dimensionality
- reproducing kernel hilbert space
- input space
- sparse representation
- parameter space
- dimensionality reduction
- kernel methods
- clustering algorithm
- geodesic distance
- vector space
- dimension reduction
- data points
- diffusion tensor
- covariance matrix
- distribution function
- lie group
- similarity search
- metric space
- mean shift
- nearest neighbor
- support vector machine
- probabilistic model
- feature extraction