We describe a method for selecting optimal actions affecting the sensors in a probabilistic state estimation framework, with an application in selecting optimal zoom levels for a ...
Benjamin Deutsch, Matthias Zobel, Joachim Denzler,...
Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances ...
Jean Ponce, Tamara L. Berg, Mark Everingham, David...
We describe an enhanced method for the selection of optimal sensor actions in a probabilistic state estimation framework. We apply this to the selection of optimal focal lengths f...
Benjamin Deutsch, Heinrich Niemann, Joachim Denzle...
Abstract. This paper presents a fast object class localization framework implemented on a data parallel architecture currently available in recent computers. Our case study, the im...
Current moving-object indexing concentrates on point-objects capable of continuous movement in one-, two-, and three-dimensional Euclidean spaces, and most approaches are based on...