• DocumentCode
    1742979
  • Title

    Foreground-background segmentation by cellular neural networks

  • Author

    Giaccone, P.R. ; Tsaptsinos, D. ; Jones, G.A.

  • Author_Institution
    Kingston Univ., UK
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    438
  • Abstract
    A common procedure in digital postproduction is rotoscoping, the segmentation of independently moving foreground elements from background in a sequence of images. Still often carried our manually, rotoscoping is time-consuming and requires great skill in determining the boundary between foreground and background. Errors lead to a bubbling artefact in the final composited sequence. The industry is interested in automated rotoscoping. Any automatic segmentation method must correctly locate the boundary and be robust given rapid motion and non-static backgrounds. A cellular neural network for segmentation is presented that labels pixels by colour, estimated motion and neighbouring labels. The method is accurate, labour saving and many times faster than manual rotoscoping
  • Keywords
    cellular neural nets; image segmentation; motion estimation; bubbling artefact; digital postproduction; foreground-background segmentation; rotoscoping; Cellular neural networks; Computer science; Design for disassembly; Image segmentation; Labeling; Motion compensation; Motion estimation; Pixel; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2000. Proceedings. 15th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-0750-6
  • Type

    conf

  • DOI
    10.1109/ICPR.2000.906106
  • Filename
    906106