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