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SIGIR
2011
ACM

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

7 years 9 months ago
Bag-of-visual-words vs global image descriptors on two-stage multimodal retrieval
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 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. Categories and Subject Descriptors: H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval—retrieval models, search process General Terms: Measurement, Experimentation, Theory
Savvas A. Chatzichristofis, Konstantinos Zagoris,
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where SIGIR
Authors Savvas A. Chatzichristofis, Konstantinos Zagoris, Avi Arampatzis
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