Moving Past Principal Component Analysis: Nonlinear Dimensionality Reduction Towards Better Hand Pose Synthesis.
Edoardo BattagliaMichael KasmanAnn Majewicz FeyPublished in: ISMR (2022)
Keyphrases
- nonlinear dimensionality reduction
- principal component analysis
- hand pose
- dimensionality reduction
- low dimensional
- dimensionality reduction methods
- manifold learning
- pose estimation
- locally linear embedding
- position and orientation
- high dimensional data
- dimension reduction
- principal components
- human hand
- linear discriminant analysis
- high dimensional
- degrees of freedom
- hand tracking
- covariance matrix
- feature extraction
- feature selection
- feature space
- face images
- moving objects
- face recognition
- discriminant analysis
- sparse representation
- viewpoint
- random projections
- riemannian manifolds