CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Hierarchical clustering-based navigation of image search results
Haoyang Ding; Jing Liu; Hanqing Lu
Conference NameInternational Conference on Multimedia
Source PublicationProceedings of the 16th International Conference on Multimedia 2008
Conference DateOctober 26-31, 2008
Conference PlaceVancouver, British Columbia, Canada
AbstractUsually, the image search results contain multiple topics on semantic level and even semantically consistent images have diverse appearances on visual level. How to organize the results into semantically and visually consistent clusters becomes a necessary task to facilitate users' navigation. To attack this, HiCluster, an effective method to organize image search results is designed in this paper, which employs both textual and visual analysis. First, we extract some query-related key phrases to enumerate specific semantics of the given query and cluster them into some semantic clusters using K-lines-based clustering algorithm. Second, the resulting images corresponding to each key phrase are clustered with Bregman Bubble Clustering (BBC) algorithm, which partially groups images in the whole set while discarding some scattered noisy ones. At last, a novel user interface (UI) is designed to provide users with the diverse and helpful information based on the hierarchical clustering structure. Experiments on web images demonstrate the effectiveness and potential of the system.
KeywordImage Search Search Result Clustering User Interface
Document Type会议论文
Corresponding AuthorJing Liu
Recommended Citation
GB/T 7714
Haoyang Ding,Jing Liu,Hanqing Lu. Hierarchical clustering-based navigation of image search results[C],2008.
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