• DocumentCode
    2101500
  • Title

    Motion analysis: model selection and motion segmentation

  • Author

    Gheissari, Niloofar ; Bab-Hadiashar, Alireza

  • Author_Institution
    Sch. of Eng. & Sci., Swinburne Univ. of Technol., Hawthorn, Vic., Australia
  • fYear
    2003
  • fDate
    17-19 Sept. 2003
  • Firstpage
    442
  • Lastpage
    447
  • Abstract
    A new model selection criterion based on physical characteristics of underlying motion models is proposed. The proposed criterion is then incorporated in a robust motion segmentation scheme, which is based upon robust least K-th order statistical model fitting. The proposed model criterion has been compared with many other competing techniques and is shown to be more suitable for the motion segmentation task. The motion segmentation algorithm has been tested (and shown to be successful) on a number of synthetic and real image sequences.
  • Keywords
    computer vision; image motion analysis; image segmentation; image sequences; statistical analysis; computer vision; least K-th order statistical model fitting; model selection; motion analysis; real image sequences; robust motion segmentation; synthetic image sequences; Application software; Computer vision; Image motion analysis; Image sequences; Layout; Motion analysis; Motion segmentation; Pattern recognition; Robustness; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Processing, 2003.Proceedings. 12th International Conference on
  • Print_ISBN
    0-7695-1948-2
  • Type

    conf

  • DOI
    10.1109/ICIAP.2003.1234090
  • Filename
    1234090