Document Type

Conference Paper

Department/Unit

Department of Computer Science

Title

Multi-level semantic characterisation and refinement for Web image search

Language

English

Abstract

With the increasing number of Web images and social photograph sharing sites, effective search of real-world images becomes a formidable challenge and an important necessity. Different indexing and annotation algorithms are required for different types of Web images. To meet the challenge and provide satisfactory search results to users, we present a multi-level method with four levels differentially applied to different types of Web images. The performance of our method is evaluated by experiments on thousands of Web images and tags in different subsets, and our approach is able to yield highly promising results compared with applying a single method to all types of Web images. © 2011 Published by Elsevier Ltd.

Keywords

Automatic annotation, CYC inference, Image retrival, MPEG-7, Scene analysis

Publication Date

2011

Source Publication Title

2011 2nd International Conference on Challenges in Environmental Science and Computer Engineering (CESCE 2011)

Start Page

147

End Page

154

Conference Location

Haikou, China

Publisher

Elsevier

DOI

10.1016/j.proenv.2011.12.023

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