A Web Image Retrieval Re-ranking Scheme with Cross-Modal Association Rules

被引：2
|
作者：
Zhu, Yong [1 ]
Xiong, Naixue [1 ,2 ]
Park, Jong Hyuk [3 ]
He, Ruhan [1 ]
机构：
[1] Wuhan Univ Sci & Engn, Coll Comp Sci, Wuhan 430073, Peoples R China
[2] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30303 USA
[3] Kyungnam Univ, Dept Comp Sci & Engn, Kyungnam, South Korea
来源：
INTERNATIONAL SYMPOSIUM ON UBIQUITOUS MULTIMEDIA COMPUTING, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/UMC.2008.25
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a new re-ranking scheme and presents experimental performance results fir web image retrieval with integrated query. In our previous work, cross-modal association rule was designed for associating one keyword with several visual feature clusters in web image retrieval. Based on the cross-modal association rule, we implement an automatic re-ranking process online to integrate the keyword and visual features for web image retrieval, and gives experimental test. The experiment is carried out in a web image retrieval system named VAST (VisuAl & SemanTic image search), and the results show the effectiveness of the re-ranking method scheme.
引用
收藏
页码：83 / +
页数：2
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