When Regression Meets Manifold Learning for Object Recognition and Pose Estimation.
Mai BuiSergey ZakharovShadi AlbarqouniSlobodan IlicNassir NavabPublished in: CoRR (2018)
Keyphrases
- manifold learning
- object recognition and pose estimation
- pose estimation
- low dimensional
- dimensionality reduction
- nonlinear dimensionality reduction
- high dimensional
- semi supervised
- regression model
- high dimensional data
- diffusion maps
- laplacian eigenmaps
- subspace learning
- head pose estimation
- manifold structure
- neural network
- support vector regression
- dimension reduction
- model selection
- feature space
- feature extraction
- gaussian processes
- sparse representation
- data mining
- pairwise
- support vector
- three dimensional
- learning algorithm
- data sets
- least squares
- manifold embedding
- nonlinear manifold