Information Fusion in Multimedia Information Retrieval

  • Jana Kludas
  • Eric Bruno
  • Stéphane Marchand-Maillet
Conference paper

DOI: 10.1007/978-3-540-79860-6_12

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4918)
Cite this paper as:
Kludas J., Bruno E., Marchand-Maillet S. (2008) Information Fusion in Multimedia Information Retrieval. In: Boujemaa N., Detyniecki M., Nürnberger A. (eds) Adaptive Multimedia Retrieval: Retrieval, User, and Semantics. AMR 2007. Lecture Notes in Computer Science, vol 4918. Springer, Berlin, Heidelberg

Abstract

In retrieval, indexing and classification of multimedia data an efficient information fusion of the different modalities is essential for the system’s overall performance. Since information fusion, its influence factors and performance improvement boundaries have been lively discussed in the last years in different research communities, we will review their latest findings. They most importantly point out that exploiting the feature’s and modality’s dependencies will yield to maximal performance. In data analysis and fusion tests with annotated image collections this is undermined.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jana Kludas
    • 1
  • Eric Bruno
    • 1
  • Stéphane Marchand-Maillet
    • 1
  1. 1.University of GenevaSwitzerland

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