High Dimensional Correspondences from Low Dimensional Manifolds - An Empirical Comparison of Graph-Based Dimensionality Reduction Algorithms.
Ribana RoscherFalko SchindlerWolfgang FörstnerPublished in: ACCV Workshops (2) (2010)
Keyphrases
- high dimensional
- dimensionality reduction
- low dimensional manifolds
- low dimensional
- manifold learning
- high dimensional data
- intrinsic dimensionality
- feature extraction
- high dimensionality
- noisy data
- high dimensional spaces
- input space
- nonlinear dimensionality reduction
- principal component analysis
- data sets
- dimension reduction
- dimensionality reduction methods
- benchmark datasets
- parameter space
- input image
- pairwise
- feature space
- machine learning