Principal component analyses (PCA) has been widely used in reduction of the dimensionality of datasets, classification, feature extraction, etc. It has been combined with many oth...
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering...
Ming-Hsuan Yang, Narendra Ahuja, David J. Kriegman
An important problem in medical imaging is that of ef?cient volumetric image compression. In addition to compression ef?ciency, scalable representations which allow access to the ...
Corresponding image points of a rigid object in a discrete sequence of images fulfil the so-called multilinear constraint. In this paper the continuous time analogue of this const...