Computing a high-dimensional euclidean embedding from an arbitrary smooth riemannian metric.
Zichun ZhongWenping WangBruno LévyJing HuaXiaohu GuoPublished in: ACM Trans. Graph. (2018)
Keyphrases
- riemannian metric
- high dimensional
- vector space
- low dimensional
- square root
- euclidean space
- parameter space
- similarity search
- smooth curves
- metric space
- shape representation
- fisher information
- multidimensional scaling
- high dimensional data
- data points
- covariance matrices
- dimensionality reduction
- euclidean distance
- positive definite
- shape space
- feature space
- diffusion tensor
- infinite dimensional
- tensor field
- lie group
- input space
- manifold learning
- point correspondences