This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
We introduce a formalism for optimal sensor parameter selection for iterative state estimation in static systems. Our optimality criterion is the reduction of uncertainty in the st...
The problem of recognizing classes of objects as opposed to special instances requires methods of comparing images that capture the variation within the class while they discrimina...
Recognizing activities based on an actor’s interaction with everyday objects is an important research approach within ubiquitous computing. We present a recognition approach whic...
Dipak Surie, Fabien Lagriffoul, Thomas Pederson, D...
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...