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Bag-of-visual-words vs global image descriptors on two-stage multimodal retrieval

dc.contributor.authorZagoris, Konstantinos
dc.contributor.authorChatzichristofis, Savvas A.
dc.contributor.authorArampatzis, Avi
dc.description.abstractThe Bag-Of-Visual-Words (BOVW) paradigm is fast becoming a popular image representation for Content-Based Image Retrieval (CBIR), mainly because of its better retrieval effectiveness over global feature representations on collections with images being nearduplicate to queries. In this experimental study we demonstrate that this advantage of BOVW is diminished when visual diversity is enhanced by using a secondary modality, such as text, to pre-filter images. The TOP-SURF descriptor is evaluated against Compact Composite Descriptors on a two-stage image retrieval setup, which first uses a text modality to rank the collection and then perform CBIR only on the top-K items.en_UK
dc.publisherACM SIGIR 2011en_UK
dc.relation.ispartofseriesSIGIR '11 Proceedings of the 34th international ACM SIGIR conference on;Research and development in Information Retrieval,Beijing, China — July 24 - 28, 2011
dc.subjectResearch Subject Categories::TECHNOLOGYen_UK
dc.subjectImage Retrievalen_UK
dc.subjectTwo-Stage Retrievalen_UK
dc.titleBag-of-visual-words vs global image descriptors on two-stage multimodal retrievalen_UK
dc.typeWorking Paperen_UK

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