Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
We develop a framework for the automatic discovery of query classes for query-class-dependent search models in multimodal retrieval. The framework automatically discovers useful q...
Feature trajectories have shown to be efficient for representing videos. Typically, they are extracted using the KLT tracker or matching SIFT descriptors between frames. However,...
Heng Wang, Alexander Kläser, Cordelia Schmid, Che...
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...
In this paper we introduce a novel Riemannian framework for shape analysis of parameterized surfaces. We derive a distance function between any two surfaces that is invariant to r...
Sebastian Kurtek, Eric Klassen, Anuj Srivastava, Z...