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Bag-of-visual-words vs global image descriptors on two-stage multimodal retrieval
2011
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11
The 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
doi:10.1145/2009916.2010144
dblp:conf/sigir/ChatzichristofisZA11
fatcat:xcu2cu7shfgg3flxit46dlzviu