Multilevel Relevance Feedback for 3D Shape Retrieval

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dc.contributor.authorGiorgi, Danielaen_US
dc.contributor.authorFrosini, Patrizioen_US
dc.contributor.authorSpagnuolo, Michelaen_US
dc.contributor.authorFalcidieno, Biancaen_US
dc.contributor.editorMichela Spagnuolo and Ioannis Pratikakis and Remco Veltkamp and Theoharis Theoharisen_US
dc.date.accessioned2013-10-21T18:00:32Z
dc.date.available2013-10-21T18:00:32Z
dc.date.issued2009en_US
dc.description.abstractRelevance feedback techniques are expected to play an important role in 3D search engines, as they help to bridge the semantic gap between the user and the system: similarity is a cognitive process, depending on the observer. We propose a novel relevance feedback technique, whose basic idea is threefold. First of all, the user is provided with a variety of shape descriptors, analysing different shape properties. The user then expresses her similarity concept through a friendly interface which supports multilevel relevance judgements. Finally, the system inhibits the role of the shape properties that do not reflect the user's idea of similarity. The assumption is that similarity may emerge as an inhibition of differences, i.e., as a lack of diversity with respect to the shape properties taken into account. The proposed technique is based on a simple scaling procedure, which does not require any a priori learning or optimization of parameters.en_US
dc.description.seriesinformationEurographics 2009 Workshop on 3D Object Retrievalen_US
dc.identifier.isbn978-3-905674-16-3en_US
dc.identifier.issn1997-0463en_US
dc.identifier.urihttps://doi.org/10.2312/3DOR/3DOR09/045-052en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): H.3.3 [Information Systems]: Information Search and Retrieval - Relevance feedbacken_US
dc.titleMultilevel Relevance Feedback for 3D Shape Retrievalen_US
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