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Hand tracking in virtual reality

Verfolgung der Hände in der virtuellen Realität
Authors: Markovic, Dana;

Hand tracking in virtual reality

Abstract

Diese Arbeit präsentiert eine Lösung für die Erkennung von Handgesten nur mithilfe von Bildverarbeitungsmethoden. Die Lösung besteht aus Handextraktion und Gestenerkennung, sowie aus einer Modellierung der Hand in 3D. Das vorgeschlagene Anwendungsgebiet wäre virtuelle Realität. Die Hauptmethoden, die für die Handextraktion benutzt wurden, sind Hintergrundsubtraktion und die Hauptkomponentenanalyse (Principal component analysis). Für die Gestenerkennung werden eine Lösung mit dem Levenberg- Marquardt Algorithmus und eine iterative Heuristik präsentiert. In der Evaluation wurden sowohl verschiedene Gesten, als auch verschiedene Umgebungseinrichtungen getestet.

This work presents a solution of hand gesture recognition by using only image processing techniques. It consists of hand extraction and gesture recognition, as well as modelling the hand in 3D. The proposed field to be applied is Virtual Reality. Main techniques used for hand extraction are background subtraction and Principal component analysis. For gesture recognition a solution using the Levenberg-Marquardt algorithm, and an- other using an Iterative Heuristic are presented. In the evaluation part different gestures are tested, as well as different surrounding setups.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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