• DocumentCode
    1944002
  • Title

    Image Registration with Uncalibrated Cameras in Hybrid Vision Systems

  • Author

    Chen, Datong ; Yang, Jie

  • Author_Institution
    Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA
  • Volume
    1
  • fYear
    2005
  • fDate
    5-7 Jan. 2005
  • Firstpage
    427
  • Lastpage
    432
  • Abstract
    This paper addresses the problem of robust registering of images among perspective and omnidirectional cameras in a hybrid vision system (HVS). Nonlinearity in an HVS introduced by omnidirectional cameras poses challenges for computing pixel correspondences among images. In previous HVSs, cameras must be calibrated by performing registration. In this paper, we propose a non-linear approach for registering images in an HVS without requiring calibration of cameras. We first discuss the homographies between omnidirectional and perspective images under a local planar assumption. We then propose a robust patch level registration algorithm by exploiting a constraint on large 3D spatial planes. The proposed approach enables an HVS for applications that require quick deployment or active cameras. Experimental results have demonstrated feasibility of the proposed approach
  • Keywords
    cameras; computer vision; image registration; hybrid vision system; image homography; image registration; local planar assumption; omnidirectional camera; patch level registration algorithm; uncalibrated camera; Calibration; Cameras; Computer science; Computer vision; Image registration; Layout; Machine vision; Mirrors; Pixel; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Application of Computer Vision, 2005. WACV/MOTIONS '05 Volume 1. Seventh IEEE Workshops on
  • Conference_Location
    Breckenridge, CO
  • Print_ISBN
    0-7695-2271-8
  • Type

    conf

  • DOI
    10.1109/ACVMOT.2005.59
  • Filename
    4129513