• DocumentCode
    3495471
  • Title

    Content-based 3D mosaic representation for video of dynamic 3D scenes

  • Author

    Zhu, Zhigang ; Tang, Hao ; Wolberg, George ; Layne, Jeffery R.

  • Author_Institution
    Dept. of Comput. Sci., City Coll. of New York
  • fYear
    2005
  • fDate
    1-1 Dec. 2005
  • Lastpage
    203
  • Abstract
    We propose a content-based 3D mosaic representation for long video sequences of 3D and dynamic scenes captured by a camera on a mobile platform. The motion of the camera has a dominant direction of motion (as on an airplane or ground vehicle), but 6 degrees-of-freedom (DOF) motion is allowed. In the first step, a pair of generalized parallel-perspective (pushbroom) stereo mosaics is generated that captured both the 3D and dynamic aspects of the scene under the camera coverage. In the second step, a segmentation-based stereo matching algorithm is applied to extract parametric representation of the color, structure and motion of the dynamic and/or 3D objects in urban scenes where a lot of planar surfaces exist. Based on these results, the content-based 3D mosaic (CB3M) representation is created, which is a highly compressed visual representation for very long video sequences of dynamic 3D scenes. Experimental results are given
  • Keywords
    data compression; image matching; image representation; image segmentation; video signal processing; color representation; compressed visual representation; content-based 3D mosaic representation; content-based video coding; dynamic 3D scenes; image fusion; motion representation; multiimage registration; parallel-perspective stereo mosaics; stereo matching; structure representation; urban scenes; video sequences; video surveillance; Airplanes; Cameras; Image coding; Land vehicles; Layout; Streaming media; Vehicle dynamics; Video compression; Video sequences; Video surveillance; Image fusion; content-based video coding; multi-image registration; video surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applied Imagery and Pattern Recognition Workshop, 2005. Proceedings. 34th
  • Conference_Location
    Washington, DC
  • ISSN
    1550-5219
  • Print_ISBN
    0-7695-2479-6
  • Type

    conf

  • DOI
    10.1109/AIPR.2005.25
  • Filename
    1612823