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Fine-grained Visual Faceted Search

Abstract : This paper presents an interactive information retrieval scheme extending classical faceted search with fine-grained visual facets. Consistent visual words are extracted offline by constructing a matching graph at the region image level and splitting the graph in relevant clusters. Visual and textual facets are then indexed in the same faceted search engine, all of them being dynamically reranked according to their filtering efficiency before being presented to the end-user. To enhance their interpretability, each facet value is illustrated by a representative picture automatically selected from the matching graph in an adaptive way.
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Submitted on : Tuesday, July 23, 2019 - 12:09:09 PM
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Julien Champ, Alexis Joly, Pierre Bonnet. Fine-grained Visual Faceted Search. MM: Conference on Multimedia, Nov 2014, Orlando, FL, United States. pp.721-722, ⟨10.1145/2647868.2654875⟩. ⟨hal-01088822⟩



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