We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
- An architecture system and a method for tracking people are presented for sports applications. The system’s input is video data from static camera and the output is the real wo...
In this paper, we propose a new class of Human Interactive Proofs (HIPs) that allow a human to distinguish one computer from another. Unlike traditional HIPs, where the computer is...
We present a view-based method for steering a robot in a network of positions; this includes navigation along a prerecorded path, but also allows for arbitrary movement of the robo...
Holger Friedrich, David Dederscheck, Eduard Rosert...
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...