• DocumentCode
    651790
  • Title

    Cube Detection and Pose Estimation Using Property of a Cube with Evolutionary Method

  • Author

    Hiyama, Kazuki ; Akashi, T.

  • Author_Institution
    Iwate Univ., Iwate, Japan
  • fYear
    2013
  • fDate
    21-23 Oct. 2013
  • Firstpage
    171
  • Lastpage
    174
  • Abstract
    In this paper, we propose a pose estimation method of an object in three-dimensional space without the pre-learning for AR application in the mobile device. One of the implementation methods of augmented reality is using a two dimensional marker. A two-dimensional marker is not robust in the case of change in complicated three-dimensional rotation. In our work, this problem is solved by a three-dimensional marker using a cube. In the study of a pose estimation of the three-dimensional object, a model-based method using evolutionary method has been proposed. This method cannot estimate all poses, because the rotation angle of the target object is limited. In this paper, we propose the pose estimation method of a cube using a property of cube with evolutionary method. This method is possible to estimate all pose by using property related to rotation of the cube. We evaluated the proposed method by experiments using the static image of object in real-world.
  • Keywords
    augmented reality; edge detection; evolutionary computation; pose estimation; augmented reality; cube detection; cube property; evolutionary method; genetic algorithm; mobile device; model-based method; pose estimation; three-dimensional marker; three-dimensional rotation; three-dimensional space; two-dimensional marker; Accuracy; Computational modeling; Computers; Estimation; Genetic algorithms; Image color analysis; Mobile handsets; 3D Pose Estimation; Augmented Reality; Genetic Algorithm; Model-based; Silhouette Matching; Template Matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cyberworlds (CW), 2013 International Conference on
  • Conference_Location
    Yokohama
  • Print_ISBN
    978-1-4799-2245-1
  • Type

    conf

  • DOI
    10.1109/CW.2013.24
  • Filename
    6680111