Maximum Covariance Unfolding Regression: A Novel Covariate-based Manifold Learning Approach for Point Cloud Data.
Qian WangKamran PaynabarPublished in: CoRR (2023)
Keyphrases
- signal processing
- manifold learning
- point cloud data
- sparse representation
- point cloud
- dimensionality reduction
- nonlinear dimensionality reduction
- hough transform
- low dimensional
- diffusion maps
- dimension reduction
- regression model
- subspace learning
- semi supervised
- high dimensional
- laplacian eigenmaps
- computer vision
- high dimensional data
- feature extraction
- head pose estimation
- model selection
- pairwise
- support vector regression
- manifold structure
- gaussian processes
- neural network
- locally linear embedding
- feature selection
- supervised learning
- covariance matrices
- training data
- video sequences
- decision trees
- covariance matrix
- low dimensional manifolds
- manifold embedding
- nearest neighbor