We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the eme...
Many learning tasks for computer vision problems can be described by multiple views or multiple features. These views can be exploited in order to learn from unlabeled data, a.k.a....
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
In this paper we present a novel face classification system
where we represent face images as a spatial arrangement
of image patches, and seek a smooth non-linear functional
map...
In the past decade or so, subspace methods have been largely used in face recognition ? generally with quite success. Subspace approaches, however, generally assume the training d...