A Conceptual Framework for Automatic Text-Based Indexing and Retrieval in Digital Video Collections

  • Mohammed Belkhatir
  • Mbarek Charhad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4653)


The growing need for ’intelligent’ video retrieval systems leads to new architectures combining multiple characterizations of the video content that rely on expressive frameworks while providing fully-automated indexing and retrieval processes. As a matter of fact, addressing the problem of combining modalities for video indexing and retrieval is of huge importance and the only solution for achieving significant retrieval performance. This paper presents a multi-facetted conceptual framework integrating multiple characterizations of the visual and audio contents for automatic video retrieval. It relies on an expressive representation formalism handling high-level video descriptions and a full-text query framework in an attempt to operate video indexing and retrieval beyond trivial low-level processes, keyword-annotation frameworks and state-of-the art architectures loosely-coupling visual and audio descriptions.


Color Word Semantic Concept Video Model Video Retrieval Video Shot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Mohammed Belkhatir
    • 1
  • Mbarek Charhad
    • 2
  1. 1.Monash University, School of Information Technology 
  2. 2.FSM, Computer Science DepartmentTunisia

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