• DocumentCode
    3741300
  • Title

    Evaluation of feature-based object identification for augmented reality applications on mobile devices

  • Author

    Bhagya Hettige;Hansika Hewamalage;Chathuranga Rajapaksha;Nuwan Wajirasena;Akila Pemasiri;Indika Perera

  • Author_Institution
    Department of Computer Science and Engineering, University of Moratuwa, Sri Lanka
  • fYear
    2015
  • Firstpage
    170
  • Lastpage
    175
  • Abstract
    With the technological advancement in mobile computing industry the field of electronic commerce has gone through a paradigm shift. Today´s customers are more inclined towards using sophisticated mobile assistants, to help them in shopping, indoor navigation etc. rather than struggling on their own. In the literature it can be found that several attempts have been taken to address this cause. Majority of those attempts are based on marker based object identification. But current scale and the trends of the electronic commerce industry demand shopping assistants who are following markerless object identification methods due to limitations like the limited number of objects that can be identified. In order to support more usable electronic commerce applications, this paper focuses on the feasibility of deploying common and readily available feature tracking algorithms which can provide the object identification capability without having fiducial markers.
  • Keywords
    "Target tracking","Image recognition","Target recognition","Atmospheric measurements","Particle measurements","Integrated circuits"
  • Publisher
    ieee
  • Conference_Titel
    Industrial and Information Systems (ICIIS), 2015 IEEE 10th International Conference on
  • Print_ISBN
    978-1-5090-1741-6
  • Type

    conf

  • DOI
    10.1109/ICIINFS.2015.7399005
  • Filename
    7399005