Multimodal Image Retrieval Based on Keywords and Low-Level Image Features (CROSBI ID 631570)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Pobar, Miran ; Ivašić-Kos, Marina
engleski
Multimodal Image Retrieval Based on Keywords and Low-Level Image Features
Image retrieval approaches dealing with the complex problem of image search and retrieval in very large image datasets proposed so far can be roughly divided into those that use text descriptions of images (text-based image retrieval) and those that compare visual image content (content-based image retrieval). Both approaches have their strengths and drawbacks especially in the case of searching for images in general unconstrained domain. To take advantage of both approaches, we propose a multimodal framework that uses both keywords and visual properties of images. Keywords are used to determine the semantics of the query while the example image presents the visual impression (perceptual and structural information) that retrieved images should suit. In the paper, the over-view of the proposed multimodal image retrieval framework is presented. For computing the content-based similarity between images different feature sets and metrics were tested. The procedure is described with Corel and Flickr images from the domain of outdoor scenes.
image retrieval ; multimodal query ; content-based similarity
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Podaci o prilogu
133-140.
2015.
objavljeno
10.1007/978-3-319-27932-9_12
Podaci o matičnoj publikaciji
Semantic Keyword-based Search on Structured Data Sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers
Cardoso, J., Guerra, F., Houben, G.-J., Pinto, A.M., Velegrakis, Y. (Eds.)
Coimbra: Springer
978-3-319-27931-2
Podaci o skupu
First COST Action IC1302 International KEYSTONE Conference, IKC 2015
predavanje
08.09.2015-09.09.2015
Coimbra, Portugal
Povezanost rada
Informacijske i komunikacijske znanosti, Računarstvo