• DocumentCode
    1598801
  • Title

    A Kalman-filtering method for 3D camera motion estimation from image sequences

  • Author

    Kim, Eung Tae ; Han, Jong-Ki ; Kim, Hyung-Myung

  • Author_Institution
    Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea
  • Volume
    3
  • fYear
    1997
  • Firstpage
    630
  • Abstract
    In this paper, we describe a method for estimating and compensating 3D camera motion in image sequences for applications to the video coding system. To effectively estimate camera motion parameters (zoom, pan, tilt, swing, and focal length) from image sequences, we propose a new linear motion parameter equation and use the Kalman filtering method to solve it. Unlike the existing linear techniques, the proposed linear method accurately estimates the large rotation angles and the focal length. Experimental results show that the proposed method outperforms the conventional linear methods, especially for a large rotation angle
  • Keywords
    Kalman filters; image sequences; motion compensation; motion estimation; parameter estimation; stereo image processing; video coding; 3D camera motion estimation; Kalman-filtering method; focal length; image sequences; large rotation angles; linear motion parameter equation; motion compensation; pan; swing; tilt; video coding system; zoom; Cameras; Geometry; Image coding; Image sequences; Iterative methods; Kalman filters; Motion estimation; Nonlinear equations; Parameter estimation; Video coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1997. Proceedings., International Conference on
  • Conference_Location
    Santa Barbara, CA
  • Print_ISBN
    0-8186-8183-7
  • Type

    conf

  • DOI
    10.1109/ICIP.1997.632200
  • Filename
    632200