Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
We propose a pixel similarity-based algorithm enabling accurate rigid registration between single and multimodal images. The method relies on the partitioning of a reference image...
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...