• DocumentCode
    1368366
  • Title

    Motion segmentation based on motion/brightness integration and oscillatory correlation

  • Author

    Çesmeli, Erdogan ; Wang, DeLiang

  • Author_Institution
    Biomed. Eng. Center, Ohio State Univ., Columbus, OH, USA
  • Volume
    11
  • Issue
    4
  • fYear
    2000
  • fDate
    7/1/2000 12:00:00 AM
  • Firstpage
    935
  • Lastpage
    947
  • Abstract
    A segmentation method based on the integration of motion and brightness is proposed for image sequences. The method is composed of two parallel pathways that process motion and brightness, respectively, Inspired by the visual system, the motion pathway has two stages. The first stage estimates local motion at locations with reliable information. The second stage performs segmentation based on local motion estimates. In the brightness pathway, the input scene is segmented into regions based on brightness distribution. Subsequently, segmentation results from the two pathways are integrated to refine motion estimates. The final segmentation is performed in the motion network based on refined estimates. For segmentation, locally excitatory globally inhibitory oscillator network (LEGION) architecture is employed whereby the oscillators corresponding to a region of similar motion/brightness oscillate in synchrony and different regions attain different phases. Results on synthetic and real image sequences are provided, and comparisons with other methods are made
  • Keywords
    correlation methods; image segmentation; image sequences; motion estimation; neural nets; synchronisation; LEGION; brightness; image segmentation; image sequences; locally excitatory globally inhibitory oscillator network; motion estimation; neural networks; oscillatory correlation; synchronisation; Apertures; Brightness; Computer vision; Image segmentation; Image sequences; Layout; Local oscillators; Motion estimation; Motion segmentation; Neural networks;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.857773
  • Filename
    857773