2008 | OriginalPaper | Buchkapitel
Information Fusion in Multimedia Information Retrieval
verfasst von : Jana Kludas, Eric Bruno, Stéphane Marchand-Maillet
Erschienen in: Adaptive Multimedia Retrieval: Retrieval, User, and Semantics
Verlag: Springer Berlin Heidelberg
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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.