• DocumentCode
    1742137
  • Title

    From video shot clustering to sequence segmentation

  • Author

    Veneau, Emmanuel ; Ronfard, Rémi ; Bouthemy, Patrick

  • Author_Institution
    Inst. Nat. de l´´Audiovisuel, Bry-sur-Marne, France
  • Volume
    4
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    254
  • Abstract
    Segmenting video documents into sequences from elementary shots to supply an appropriate higher level description of the video is a challenging task. The paper presents a two-stage method. First, we build a binary agglomerative hierarchical time-constrained shot clustering. Second, based on the cophenetic criterion, a breaking distance between shots is computed to detect sequence changes. Various options are implemented and compared. Real experiments have proved that the proposed criterion can be efficiently used to achieve appropriate segmentation into sequences
  • Keywords
    image segmentation; image sequences; pattern clustering; binary agglomerative hierarchical time-constrained shot clustering; breaking distance; cophenetic criterion; higher level description; sequence changes; sequence segmentation; two-stage method; video shot clustering; Buildings; Data mining; Feature extraction; Gunshot detection systems; Indexing; Layout; Merging; Symmetric matrices;
  • 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.2000.902907
  • Filename
    902907