Fusion of Locally Linear Embedding and Principal Component Analysis for Face Recognition (FLLEPCA).
Eimad Eldin AbushamDavid Ngo Chek LingAndrew Teoh Beng JinPublished in: ICAPR (2) (2005)
Keyphrases
- principal component analysis
- locally linear embedding
- face recognition
- dimensionality reduction
- dimensional reduction
- low dimensional
- linear discriminant analysis
- face images
- locality preserving projections
- nonlinear dimensionality reduction
- subspace learning
- dimensionality reduction methods
- face databases
- discriminant analysis
- neighborhood preserving embedding
- principal components
- dimension reduction
- manifold learning
- facial pose
- feature extraction
- high dimensional data
- covariance matrix
- fusion method
- singular value decomposition
- subspace methods
- computer vision
- sparse representation
- image fusion
- preprocessing step
- principal components analysis
- image processing
- feature space
- high dimensional
- kernel pca
- similarity measure
- random projections
- data sets