• DocumentCode
    2324124
  • Title

    Hierarchical Ontology-Based Robust Video Shots Indexation Using Global MPEG-7 Visual Descriptors

  • Author

    Benmokhtar, Rachid ; Huet, Benoit

  • Author_Institution
    Dept. Multimedia, EURECOM, Sophia-Antipolis
  • fYear
    2009
  • fDate
    3-5 June 2009
  • Firstpage
    195
  • Lastpage
    200
  • Abstract
    This paper proposes to improve our previous work on the concept-based video shot indexing, by considering an ontological concept construction in the TRECVid 2007 video retrieval, based on two steps. First, each single concept is modeled independently. Second, an ontology-based concept is introduced via the representation of the influence relations between concepts and the ontological readjustment of the confidence values. The main contribution of this paper is in the exploitation manner of the inter-concepts similarity in our indexing system, where three measures are represented: co-occurrence, visual similarity and LSCOM-lite ontology path length contribution. The experimental results report the efficiency and the significant improvement provided by the proposed scheme.
  • Keywords
    indexing; ontologies (artificial intelligence); video retrieval; video signal processing; LSCOM-lite ontology path length contribution; TRECVid 2007 video retrieval; global MPEG-7 visual descriptor; hierarchical ontology; robust video shot indexation; visual similarity; Bayesian methods; Content based retrieval; Data mining; Feature extraction; Indexing; Information retrieval; Length measurement; MPEG 7 Standard; Ontologies; Robustness; LSCOM-lite; TRECVid; fusion; indexation; inter-concepts similarity; ontology; video shots content;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Content-Based Multimedia Indexing, 2009. CBMI '09. Seventh International Workshop on
  • Conference_Location
    Chania
  • Print_ISBN
    978-1-4244-4265-2
  • Electronic_ISBN
    978-0-7695-3662-0
  • Type

    conf

  • DOI
    10.1109/CBMI.2009.18
  • Filename
    5137840