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ECIR
2011
Springer

Dynamic Two-Stage Image Retrieval from Large Multimodal Databases

10 years 4 months ago
Dynamic Two-Stage Image Retrieval from Large Multimodal Databases
Abstract. Content-based image retrieval (CBIR) with global features is notoriously noisy, especially for image queries with low percentages of relevant images in a collection. Moreover, CBIR typically ranks the whole collection, which is inefficient for large databases. We experiment with a method for image retrieval from multimodal databases, which improves both the effectiveness and efficiency of traditional CBIR by exploring secondary modalities. We perform retrieval in a two-stage fashion: first rank by a secondary modality, and then perform CBIR only on the top-K items. Thus, effectiveness is improved by performing CBIR on a ‘better’ subset. Using a relatively ‘cheap’ first stage, efficiency is also improved via the fewer CBIR operations performed. Our main novelty is that K is dynamic, i.e. estimated per query to optimize a predefined effectiveness measure. We show that such dynamic two-stage setups can be significantly more effective and robust than similar setups...
Avi Arampatzis, Konstantinos Zagoris, Savvas A. Ch
Added 27 Aug 2011
Updated 27 Aug 2011
Type Journal
Year 2011
Where ECIR
Authors Avi Arampatzis, Konstantinos Zagoris, Savvas A. Chatzichristofis
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