Subspace Learning Based on Laplacian Eigenmaps and LDA for Face Recognition.
Yanwei PangZhengkai LiuYuefang SunPublished in: Int. J. Inf. Acquis. (2006)
Keyphrases
- subspace learning
- face recognition
- manifold learning
- linear discriminant analysis
- dimensionality reduction
- kernel pca
- locally linear embedding
- nonlinear dimensionality reduction
- subspace learning algorithm
- principal component analysis
- dimension reduction
- discriminant analysis
- feature extraction
- sparse representation
- face images
- low dimensional
- high dimensional data
- linear subspace
- computer vision
- dimensionality reduction methods
- data sets
- image processing
- subspace methods
- high dimensional
- semi supervised
- high dimensionality
- feature vectors
- latent dirichlet allocation
- data points
- feature space
- supervised learning
- pattern recognition
- signal processing
- distance measure