Abstract
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.
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Belkhatir, M., Charhad, M. (2007). A Conceptual Framework for Automatic Text-Based Indexing and Retrieval in Digital Video Collections. In: Wagner, R., Revell, N., Pernul, G. (eds) Database and Expert Systems Applications. DEXA 2007. Lecture Notes in Computer Science, vol 4653. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74469-6_39
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DOI: https://doi.org/10.1007/978-3-540-74469-6_39
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