EvoSets: Tracking the Sensitivity of Dimensionality Reduction Results Across Subspaces.
Guodao SunSujia ZhuQi JiangWang XiaRonghua LiangPublished in: IEEE Trans. Big Data (2022)
Keyphrases
- dimensionality reduction
- high dimensional data
- low dimensional
- principal component analysis
- high dimensional
- linear projection
- lower dimensional
- data points
- visual tracking
- data representation
- input space
- particle filter
- high dimensionality
- pattern recognition
- data sets
- manifold learning
- feature extraction
- feature space
- kalman filter
- pattern recognition and machine learning
- nonlinear dimensionality reduction
- mean shift
- low dimensional spaces
- real time
- dimensionality reduction methods
- motion tracking
- random projections
- original data
- motion model
- sensitivity analysis
- video surveillance
- motion estimation
- nearest neighbor
- principal components
- dimension reduction
- subspace learning
- linear subspace
- high sensitivity
- structure preserving
- linear discriminant analysis
- appearance model