• DocumentCode
    2534784
  • Title

    A region-level graph labeling approach to motion-based segmentation

  • Author

    Gelgon, Marc ; Bouthemy, Patrick

  • Author_Institution
    IRISA, Rennes, France
  • fYear
    1997
  • fDate
    17-19 Jun 1997
  • Firstpage
    514
  • Lastpage
    519
  • Abstract
    This paper deals with the problem of motion-based segmentation of image sequences. Such partitions are multiple-purpose in dynamic scene analysis. We first extract a spatial texture-based partition using an unsupervised MRF approach. The regions obtained are then grouped according to a motion-based criterion. This grouping process relies on two motion estimation techniques and exploits centextual information between regions. In contrast with clustering techniques, region grouping is formalized as a motion-based graph labeling process, within a Markovian framework. Results on real-world image sequences are shown and validate the proposed method
  • Keywords
    Markov processes; image segmentation; image sequences; motion estimation; Markovian framework; centextual information; dynamic scene analysis; image sequences; motion-based graph labeling process; motion-based segmentation; region grouping; region-level graph labeling approach; spatial texture-based partition; unsupervised MRF approach; Clustering algorithms; Computer vision; Data mining; Image analysis; Image segmentation; Image sequences; Labeling; Merging; Motion estimation; Partitioning algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
  • Conference_Location
    San Juan
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-7822-4
  • Type

    conf

  • DOI
    10.1109/CVPR.1997.609374
  • Filename
    609374