Visual semantic complex network for web images
Refereed conference paper presented and published in conference proceedings

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AbstractThis paper proposes modeling the complex web image collections with an automatically generated graph structure called visual semantic complex network (VSCN). The nodes on this complex network are clusters of images with both visual and semantic consistency, called semantic concepts. These nodes are connected based on the visual and semantic correlations. Our VSCN with 33,240 concepts is generated from a collection of 10 million web images. A great deal of valuable information on the structures of the web image collections can be revealed by exploring the VSCN, such as the small-world behavior, concept community, in-degree distribution, hubs, and isolated concepts. It not only helps us better understand the web image collections at a macroscopic level, but also has many important practical applications. This paper presents two application examples: content-based image retrieval and image browsing. Experimental results show that the VSCN leads to significant improvement on both the precision of image retrieval (over 200%) and user experience for image browsing. © 2013 IEEE.
All Author(s) ListQiu S., Wang X., Tang X.
Name of Conference2013 14th IEEE International Conference on Computer Vision, ICCV 2013
Start Date of Conference01/12/2013
End Date of Conference08/12/2013
Place of ConferenceSydney, NSW
Country/Region of ConferenceAustralia
Detailed descriptionorganized by IEEE,
Pages3623 - 3630
LanguagesEnglish-United Kingdom

Last updated on 2021-17-09 at 23:43