When Regression Meets Manifold Learning for Object Recognition and Pose Estimation.
Mai BuiSergey ZakharovShadi AlbarqouniSlobodan IlicNassir NavabPublished in: ICRA (2018)
Keyphrases
- manifold learning
- object recognition and pose estimation
- pose estimation
- low dimensional
- dimensionality reduction
- regression model
- semi supervised
- high dimensional
- subspace learning
- diffusion maps
- dimension reduction
- nonlinear dimensionality reduction
- head pose estimation
- high dimensional data
- support vector regression
- laplacian eigenmaps
- feature extraction
- model selection
- computer vision
- image processing
- feature space
- locally linear embedding
- three dimensional
- gaussian processes
- geodesic distance
- data mining
- manifold structure
- face recognition
- object recognition
- nonlinear manifold
- discriminant embedding
- support vector