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Evaluating the trackability of natural feature-point sets

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4 Author(s)
Gruber, L. ; Graz Univ. of Technol., Graz, Austria ; Zollmann, S. ; Wagner, Daniel ; Schmalstieg, D.

In this work we present a novel idea of evaluating natural feature-point based tracking targets. Our main objective is to evaluate the inherent characteristics of natural feature-point sets with respect to vision-based pose estimation algorithms. Our work attempts to break new ground by concentrating on evaluating complete tracking targets, rather than evaluating tracking methods or single features. This allows deriving indications on how to improve the trackability of natural feature point sets.

Published in:

Mixed and Augmented Reality, 2009. ISMAR 2009. 8th IEEE International Symposium on

Date of Conference:

19-22 Oct. 2009

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