SepHennauer

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Empirical estimation of tracking ranges and application thereof for smooth transition between two tracking devices

Student: Sven Hennauer
Supervisor: Martin Wagner
Professor: Prof. Gudrun Klinker
Submission date: 13.01.2004

Abstract

Many augmented reality applications face the problem that the tracking devices being used have limited working areas and therefore do not provide sufficient coverage. If one wants to use multiple trackers in order to extend the overall tracking area, the problem arises how to combine them, so that a smooth transition is obtained while moving from one tracking area to the other.

This thesis deals with this question and proposes two different transition strategies, which do not depend on prior knowledge of specific properties or the setup of the trackers, but instead are able to adapt to the respective tracking areas. Both strategies, being based on convex hulls and neural networks respectively, have been implemented prototypically and have been embedded into the DWARF framework. The design of this implementation allows future developers to add new transition strategies easily.

More Information

13.03.2003 Problem Statement problemstatement.pdf
13.01.2004 Submitted Thesis thesis.pdf
13.01.2004 Final Presentation slides.ppt, slides.pdf

ProjectForm
Title: Empirical estimation of tracking ranges and application thereof for smooth transition between two tracking devices
Abstract: Many augmented reality applications face the problem that the tracking devices being used have limited working areas and therefore do not provide sufficient coverage. If one wants to use multiple trackers in order to extend the overall tracking area, the problem arises how to combine them, so that a smooth transition is obtained while moving from one tracking area to the other. This thesis deals with this question and proposes two different transition strategies, which do not depend on prior knowledge of specific properties or the setup of the trackers, but instead are able to adapt to the respective tracking areas. Both strategies, being based on convex hulls and neural networks respectively, have been implemented prototypically and have been embedded into the DWARF framework. The design of this implementation allows future developers to add new transition strategies easily.
Student: Sven Hennauer
Director: Gudrun Klinker
Supervisor: Martin Wagner
Type: SEP
Status: finished
Start:  
Finish: 2004/01/13


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