CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Image Annotation Refinement using NSC-Based Word Correlation
Jing Liu; Mingjing Li; Qingshan Liu; Hanqing Lu; Songde Ma
2007
Conference NameIEEE International Conference on Multimedia and Expo
Source PublicationProceedings of the 2007 IEEE International Conference on Multimedia and Expo
Conference DateJuly 2-5, 2007
Conference PlaceBeijing, China
AbstractImage annotation refinement is crucial to improve the performance of automatic image annotation, in which the estimation of word correlation is a key issue. Typically, the word co-occurrence information may be utilized to estimate the word correlation. However, this approach is not accurate enough because it equally treats any word pair co-occurring in the training data and cannot extract synonymy relationship effectively. In this paper, a novel method is developed to estimate the word correlation based on the improved nearest spanning chains (NSC). It can extract more informative and reasonable relations among keywords. Obtaining the enhanced word correlation, a word-based graph is constructed, which is used to re-rank the candidate annotations for an untagged image. Experiments conducted on the typical Corel dataset demonstrate the effectiveness of the proposed method.
KeywordInternet Graph Theory Image Retrieval Corel Dataset Nsc-based Word Correlation Automatic Image Annotation Candidate Annotations Image Annotation Refinement Nearest Spanning Chains Synonymy Relationship Untagged Image Word Co-occurrence Information Word Correlation Estimation Word-based Graph Asia Automation Data Mining Explosions Information Retrieval Internet Organizing Statistical Distributions Thesauri Training Data
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13453
Collection模式识别国家重点实验室_图像与视频分析
Corresponding AuthorJing Liu
Recommended Citation
GB/T 7714
Jing Liu,Mingjing Li,Qingshan Liu,et al. Image Annotation Refinement using NSC-Based Word Correlation[C],2007.
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