Text-Image Interaction for Image Retrieval and Semi-Automatic Indexing
Identifieur interne : 00B563 ( Main/Exploration ); précédent : 00B562; suivant : 00B564Text-Image Interaction for Image Retrieval and Semi-Automatic Indexing
Auteurs : Gérald Duffing [France]Source :
Descripteurs français
- mix :
Abstract
This paper addresses the issue of retrieving images based on visual content, according a particular attention to the semantic dimension of information retrieval. A brief review of existing Image Retrieval Systems is provided, hilighting a major drawback of these prototypes, namely the lack of integration between classical ``semantic search'', and visual similarity retrieval (i.e. content-based retrieval). A new approach is proposed, that tries to integrate a real ``semantic'' dimension into visual content-based image retrieval. Images may be retrieved either by keyword matching (for manually indexed images), or by visual content matching. This approach is then particularly adapted to partially indexed databases, and may be used in a semi-automatic indexing tool.
Url:
Affiliations:
- France
- Grand Est, Lorraine (région)
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
Links toward previous steps (curation, corpus...)
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- to stream Hal, to step Curation: 004A73
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- to stream Main, to step Merge: 00BD22
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Le document en format XML
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<front><div type="abstract" xml:lang="en">This paper addresses the issue of retrieving images based on visual content, according a particular attention to the semantic dimension of information retrieval. A brief review of existing Image Retrieval Systems is provided, hilighting a major drawback of these prototypes, namely the lack of integration between classical ``semantic search'', and visual similarity retrieval (i.e. content-based retrieval). A new approach is proposed, that tries to integrate a real ``semantic'' dimension into visual content-based image retrieval. Images may be retrieved either by keyword matching (for manually indexed images), or by visual content matching. This approach is then particularly adapted to partially indexed databases, and may be used in a semi-automatic indexing tool.</div>
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