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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Semantic-Based Cross-Media Image Retrieval
verfasst von : Ahmed Id Oumohmed, Max Mignotte, Jian-Yun Nie
Erschienen in: Pattern Recognition and Image Analysis
Verlag: Springer Berlin Heidelberg
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In this paper, we propose a novel method for cross-media semantic-based information retrieval, which combines classical text- based and content-based image retrieval techniques. This semantic-based approach aims at determining the strong relationships between keywords (in the caption) and types of visual features associated with its typical images. These relationships are then used to retrieve images from a textual query. In particular, the association
keyword/visual feature
may allow us to retrieve non-annotated but similar images to those retrieved by a classical textual query. It can also be used for automatic images annotation. Our experiments on two different databases show that this approach is promising for cross-media retrieval.