• DocumentCode
    2236239
  • Title

    Foveated observation of shape and motion

  • Author

    Davis, James ; Chen, Xing

  • Author_Institution
    Honda Res. Inst. USA, Inc., Mountain View, CA, USA
  • Volume
    1
  • fYear
    2003
  • fDate
    14-19 Sept. 2003
  • Firstpage
    1001
  • Abstract
    Robotic navigation and interaction frequently require that the shape and motion of external objects and events be observed. Many interesting events occur at mixed scales. Subtle localized shape and motion often occurs together with long-range movements. One of the chief challenges in recovering these events is to obtain high resolution imagery suitable for resolving small details, while simultaneously increasing the working volume in which recovery is possible. This paper proposes architecture for mixed scale motion recovery. The robust coverage of a large working volume is provided by a wide area of tracking system. This system localizes interesting motions, and guides a separate foveated system of pan tilt cameras to observe the detailed event at high resolution. We demonstrate two applications, foveated structured light scanning and the capture of muscle deformation while walking. Both applications allow subtle detailed recovery that would not be possible using existing single scale systems.
  • Keywords
    image resolution; image sensors; motion estimation; robots; foveated structured light scanning; foveated system; high resolution imagery; long-range movements; mixed scale motion recovery; motion foveated observation; muscle deformation; pan tilt cameras; robotic interaction; robotic navigation; shape foveated observation; single scale systems; tracking system; Cameras; Human robot interaction; Humanoid robots; Image resolution; Muscles; Navigation; Robot vision systems; Robustness; Shape; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-7736-2
  • Type

    conf

  • DOI
    10.1109/ROBOT.2003.1241723
  • Filename
    1241723