Visualisation Techniques for Analysis and Exploration of Multimedia Data

  • Vedran Sabol
  • Wolfgang Kienreich
  • Michael Granitzer

Information technology has developed past its traditional focus on text-based data. The much-cited rapid growth of available information has been accompanied by a diversification of information types. Multimedia data is rapidly becoming the predominant form of information created, processed and distributed in many application domains.Multimedia data sets are characterized by their heterogeneous nature and complex structure. Documents often combine of different modalities, for example video streams, audio streams and textual information. Document content often features a pronounced temporal component, as in the case of audio and video data. Multimedia documents frequently include rich semantic descriptors and complex structures of cross-modal, inter- and intra-document references.

It is often not feasible to manually annotate such complex semantics, especially in the context of very large data sets. Various automated methods for the extraction of semantic metadata have been proposed and evaluated. However, the capabilities of automatic extraction are limited in terms of accuracy, performance and diversity of results. Visualisation techniques employ the vast processing power of the human visual apparatus to quickly identify complex patterns in large amounts of data. When combined with machine processing capabilities, such techniques provide unparalleled means for gaining insight into large data sets in general, and into multimedia data sets in particular.

The multi-faceted nature of multimedia documents has led to a variety of visual representations for navigating, analysing and understanding of multimedia data sets. As each representation is specifically designed to address different aspects of the data, innovative approaches combining several visualisations in a single coordinated interface had to be introduced. This chapter presents a comparative discussion of selected multimedia visual representations and tools.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Vedran Sabol
    • 1
  • Wolfgang Kienreich
    • 1
  • Michael Granitzer
    • 1
  1. 1.Know-Center GrazGrazAustria

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