• DocumentCode
    1861624
  • Title

    Fast stitching algorithm for moving object detection and mosaic construction

  • Author

    Hsieh, Jun-Wei

  • Author_Institution
    Dept. of Electr. Eng., Yuan-Ze Univ., Taoyuan, Taiwan
  • Volume
    1
  • fYear
    2003
  • fDate
    6-9 July 2003
  • Abstract
    This paper proposes a novel edge-based stitching method to detect moving objects and construct mosaics from images. The method is a coarse-to-fine scheme which first estimates a good initialization of camera parameters with two complementary methods and then refines the solution through an optimization process. The two complementary methods are the edge alignment and correspondence-based approaches, respectively. Since these two methods are complementary to each other, the desired initial estimate can be obtained more robustly. After that, a Monte-Carlo style method is then proposed for integrating these two methods together. Then, an optimization process is applied to refine the above initial parameters. Since the found initialization is very close to the exact solution and only errors on feature positions are considered for minimization, the optimization process can be very quickly achieved. Experimental results are provided to verify the superiority of the proposed method.
  • Keywords
    Monte Carlo methods; image motion analysis; minimisation; object detection; Monte-Carlo method; coarse-to-fine scheme; correspondence-based approaches; edge alignment; edge-based stitching method; fast stitching algorithm; image mosaic construction; moving object detection; optimization process; Cameras; Image coding; Image edge detection; Indexing; Object detection; Optimization methods; Robust stability; Robustness; Video compression; Virtual environment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2003. ICME '03. Proceedings. 2003 International Conference on
  • Print_ISBN
    0-7803-7965-9
  • Type

    conf

  • DOI
    10.1109/ICME.2003.1220860
  • Filename
    1220860