• DocumentCode
    3051583
  • Title

    Constrained self-calibration

  • Author

    Mendelsohn, Jeffrey ; Daniilidis, Kostas

  • Author_Institution
    GRASP Lab., Pennsylvania Univ., Philadelphia, PA, USA
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Abstract
    This paper focuses on the estimation of the intrinsic camera parameters and the trajectory of the camera from an image sequence. Intrinsic camera calibration and pose estimation are the prerequisites for many applications involving navigation tasks, scene reconstruction, and merging of virtual and real environments. Proposed and evaluated is a technical solution to decrease the sensitivity of self-calibration by placing easily identifiable targets of known shape in the environment. The relative position of the targets need not be known a priori. Assuming an appropriate ratio of size to distance these targets resolve known ambiguities. Constraints on the target placement and the cameras´ motions are explored. The algorithm is extensively tested in a variety of real-world scenarios
  • Keywords
    calibration; image reconstruction; image sequences; parameter estimation; camera calibration; constrained self-calibration; easily identifiable targets; image sequence; intrinsic camera parameters estimation; pose estimation; scene reconstruction; Calibration; Cameras; Image reconstruction; Image sequences; Laboratories; Layout; Merging; Navigation; Shape; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.
  • Conference_Location
    Fort Collins, CO
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-0149-4
  • Type

    conf

  • DOI
    10.1109/CVPR.1999.784974
  • Filename
    784974