• 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