Non-parametric Mixed-Manifold Products using Multiscale Kernel Densities.
Dehann FouriePedro Vaz TeixeiraJohn J. LeonardPublished in: IROS (2019)
Keyphrases
- multiscale
- kernel density estimation
- probability density function
- density estimates
- gaussian processes
- feature space
- laplacian eigenmaps
- probability density
- translation invariant
- scale space
- density estimation
- low dimensional
- kernel function
- natural images
- image processing
- manifold learning
- gaussian kernel
- density ratio
- coarse to fine
- nonlinear dimensionality reduction
- hilbert space
- graph embedding
- riemannian manifolds
- kernel methods
- high dimensional
- kernel pca
- wavelet coefficients
- kernel machines
- image segmentation
- parametric models
- affine invariant
- euclidean space
- input space
- image representation
- edge detection
- wavelet transform
- graph laplacian
- product information
- kernel density estimators
- semi parametric
- manifold structure
- component analysis
- multiple instance learning
- gaussian process
- shape representation
- image fusion
- mean shift
- expectation maximization
- probability distribution
- feature extraction