Title :
VAST: Automatically Combining Keywords and Visual Features for Web Image Retrieval
Author :
Jin, Hai ; He, Ruhan ; Tao, Wenbing ; Sun, Aobing
Author_Institution :
Services Comput. Technol. & Syst. Lab., Huazhong Univ. of Sci. & Technol., Wuhan
Abstract :
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.
Keywords :
Internet; image retrieval; VAST; Web image retrieval; inverted file; keyword association; large-scale Web dataset; large-scale image retrieval system; semantic contents; semantic network; visual & semantic image search; visual feature clusters; visual features; Content based retrieval; Feedback; Helium; Image databases; Image retrieval; Large-scale systems; Scalability; Search engines; Sun; World Wide Web;
Conference_Titel :
Advanced Communication Technology, 2008. ICACT 2008. 10th International Conference on
Conference_Location :
Gangwon-Do
Print_ISBN :
978-89-5519-136-3
DOI :
10.1109/ICACT.2008.4494224