Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
A novel robust active appearance model (AAM) matching algorithm is presented. The method consists of two main stages. First, initial residuals are clustered by a non parametric mea...
Reinhard Beichel, Horst Bischof, Franz Leberl, Mil...
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
For many applied problems in the context of clustering via mixture models, the estimates of the component means and covariance matrices can be affected by observations that are at...