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A graph-based image annotation framework
Liu, Jing1; Wang, Bin2; Lu, Hanqing1; Ma, Songde1
AbstractAutomatic image annotation is crucial for keyword-based image retrieval because it can be used to improve the textual description of images. In this paper, we propose a unified framework for image annotation, which contains two kinds of learning processes and incorporates three kinds of relations among images and keywords. In addition, we propose some improvements on its components, i.e. a reinforced image-to-image relation; a combined word-to-word relation; and a progressive learning method. Experiments on the Corel dataset demonstrate their effectiveness. We also show that many existing image annotation algorithms can be formulated into this framework and present an experimental comparison among these algorithms to evaluate their performance comprehensively. (c) 2007 Elsevier B.V. All rights reserved.
KeywordImage Annotation Annotation Refinement Graph Learning Image Relation Word Relation
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000253518900003
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Cited Times:15[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
2.Univ Sci & Technol China, Hefei 230027, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liu, Jing,Wang, Bin,Lu, Hanqing,et al. A graph-based image annotation framework[J]. PATTERN RECOGNITION LETTERS,2008,29(4):407-415.
APA Liu, Jing,Wang, Bin,Lu, Hanqing,&Ma, Songde.(2008).A graph-based image annotation framework.PATTERN RECOGNITION LETTERS,29(4),407-415.
MLA Liu, Jing,et al."A graph-based image annotation framework".PATTERN RECOGNITION LETTERS 29.4(2008):407-415.
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