Probabilistic PCA and ICA Subspace Mixture Models for Image Segmentation.
Dick de RidderJosef KittlerRobert P. W. DuinPublished in: BMVC (2000)
Keyphrases
- mixture model
- subspace analysis
- principal component analysis
- image segmentation
- independent component analysis
- generative model
- generalized em algorithm
- probabilistic model
- expectation maximization
- independent components
- em algorithm
- gaussian mixture model
- principle component analysis
- subspace methods
- finite mixture models
- subspace learning
- feature extraction
- density estimation
- mixture modeling
- model selection
- face recognition
- lower dimensional
- principal components analysis
- principal components
- finite mixtures
- unsupervised learning
- dimensionality reduction
- minimum message length
- gaussian mixture
- high dimensional
- low dimensional
- language model
- graph cuts
- face images
- maximum likelihood
- linear subspace
- feature space
- linear discriminant analysis
- segmentation algorithm
- image processing
- factor analysis
- topic models
- spectral clustering
- machine learning
- computer vision
- subspace clustering
- probability density function
- model based clustering
- discriminant analysis
- feature vectors
- information retrieval