Information Fusion in Multimedia Information Retrieval

  • Authors:
  • Jana Kludas;Eric Bruno;Stéphane Marchand-Maillet

  • Affiliations:
  • University of Geneva, Switzerland;University of Geneva, Switzerland;University of Geneva, Switzerland

  • Venue:
  • Adaptive Multimedial Retrieval: Retrieval, User, and Semantics
  • Year:
  • 2007

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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.