VAST: Automatically combining keywords and visual features for web image retrieval

被引：0
|
作者：
Jin, Hai [1 ]
He, Ruhan [1 ]
Tao, Wenbing [1 ]
Sun, Aobing [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Cluster & Grid Comp Lab, Serv Comp Technol & Syst Lab, Wuhan 430074, Peoples R China
来源：
10TH INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY, VOLS I-III: INNOVATIONS TOWARD FUTURE NETWORKS AND SERVICES | 2008年
关键词：
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
A large-scale image retrieval system for the WWW, named VAST (VisuAl & SemanTic image search), is presented in this paper. Based on the existing inverted file and visual feature clusters, we form a semantic network on top of the keyword association on the visual feature clusters. The system is able to automatically combine keyword and visual features for retrieval by the semantic network. The combination is automatic, simple, and very fast, which is suitable for large-scale web dataset. Meanwhile, the retrieval takes advantage of the semantic contents of the images in addition to the low-level features, which remarkably improves the retrieval precision. The experimental results demonstrate the superiority of the system.
引用
收藏
页码：2188 / 2193
页数：6
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