Subspace learning-based dimensionality reduction in building recognition.
Jing LiNigel M. AllinsonPublished in: Neurocomputing (2009)
Keyphrases
- subspace learning
- dimensionality reduction
- visual learning
- appearance based object recognition
- pattern recognition
- feature extraction
- low dimensional
- data representation
- principal component analysis
- manifold learning
- unsupervised learning
- high dimensional data
- high dimensionality
- high dimensional
- object recognition
- linear discriminant analysis
- dimensionality reduction methods
- data points
- dimension reduction
- singular value decomposition
- computer vision
- sparse representation
- feature selection
- locality preserving projections
- graph embedding
- fisher criterion
- feature space
- data analysis
- locally linear embedding
- sparse coding
- metric learning
- denoising
- learning algorithm
- linear combination
- image classification