• DocumentCode
    3139476
  • Title

    Robust estimation of a multi-layered motion representation

  • Author

    Darrell, Trevor ; Pentland, Alex

  • Author_Institution
    Media Lab., MIT, Cambridge, MA, USA
  • fYear
    1991
  • fDate
    7-9 Oct 1991
  • Firstpage
    173
  • Lastpage
    178
  • Abstract
    In order to recover an accurate representation of a scene containing multiple moving objects, one must use estimation methods that can recover both model parameters and segmentation at the same time. Traditional approaches to this problem rely on an edge-based discontinuity model, and have problems with transparent phenomena. The authors introduce a layered model of scene segmentation based on explicitly representing the support of a homogeneous region. The model employs parallel robust estimation techniques, and uses a minimal-covering optimization to estimate the number of objects in the scene. Using a simple direct motion model of translating objects, they successfully segment real image sequences containing multiple motions
  • Keywords
    image segmentation; image sequences; motion estimation; edge-based discontinuity model; estimation methods; layered model; minimal-covering optimization; model parameters; multi-layered motion representation; multiple moving objects; parallel robust estimation techniques; real image sequences; segmentation; transparent phenomena; Coherence; Computer vision; Humans; Image segmentation; Image sequences; Layout; Machine vision; Motion estimation; Robustness; Smoothing methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Motion, 1991., Proceedings of the IEEE Workshop on
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    0-8186-2153-2
  • Type

    conf

  • DOI
    10.1109/WVM.1991.212810
  • Filename
    212810