DocumentCode :
2448325
Title :
Evaluating the trackability of natural feature-point sets
Author :
Gruber, Lukas ; Zollmann, Stefanie ; Wagner, Daniel ; Schmalstie, Dieter
Author_Institution :
Graz Univ. of Technol., Graz, Austria
fYear :
2009
fDate :
19-22 Oct. 2009
Firstpage :
189
Lastpage :
190
Abstract :
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.
Keywords :
augmented reality; pose estimation; natural feature-point sets; trackability; vision-based pose estimation algorithms; Algorithm design and analysis; Computational modeling; Computer vision; Image processing; Karhunen-Loeve transforms; Object detection; Pipelines; Robustness; Runtime; Target tracking; Augmented Reality; Natural Feature Tracking Target Design; Tracking Simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mixed and Augmented Reality, 2009. ISMAR 2009. 8th IEEE International Symposium on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-5390-0
Electronic_ISBN :
978-1-4244-5389-4
Type :
conf
DOI :
10.1109/ISMAR.2009.5336469
Filename :
5336469
Link To Document :
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