• DocumentCode
    3011247
  • Title

    Zoomed Object Segmentation from Dynamic Scene Containing a Door

  • Author

    Zhang, Peng ; Emmanuel, Sabu

  • Author_Institution
    Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
  • fYear
    2008
  • fDate
    25-27 Sept. 2008
  • Firstpage
    807
  • Lastpage
    812
  • Abstract
    Accurately segmenting the moving objects from a sequence of captured video frames is a significant pre-condition for tracking and recognition of these moving objects. The challenge of segmenting the moving object is even harder when the background is dynamic and the camera used can change its zoom dynamically. Here, in this paper, we propose a new method to detect and segment moving object from a dynamic background, which contains moving multiple-leaf doors. In addition the proposed algorithm also takes care of dynamic zoom changes that can occur while shooting a scene. The proposed algorithm uses background-rebuilding with discrete door´s position to tackle moving multiple-leaf door backgrounds and image feature comparison to tackle changes in zoom. We have obtained good image sequence segmentation results with high processing speed.
  • Keywords
    image segmentation; image sequences; video signal processing; background-rebuilding; dynamic scene; dynamic zoom changes; image feature comparison; image sequence segmentation; moving multiple-leaf doors; moving object segmentation; video frames; zoomed object segmentation; Bayesian methods; Cameras; Change detection algorithms; Gaussian distribution; High performance computing; Image segmentation; Layout; Markov random fields; Object detection; Object segmentation; Dynamic Background; Segmentation; Zoom;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    High Performance Computing and Communications, 2008. HPCC '08. 10th IEEE International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-0-7695-3352-0
  • Type

    conf

  • DOI
    10.1109/HPCC.2008.115
  • Filename
    4637784