Publication | Closed Access
VAST: Automatically Combining Keywords and Visual Features for Web Image Retrieval
10
Citations
13
References
2008
Year
EngineeringMachine LearningImage RetrievalImage DatabaseSemantic WebInverted FileWeb Image RetrievalImage SearchImage AnalysisInformation RetrievalData ScienceText-to-image RetrievalPattern RecognitionVisual FeaturesCombining KeywordsMachine VisionSemantic Image SearchComputer ScienceDeep LearningComputer VisionKeyword AssociationContent-based Image RetrievalMultimedia Search
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.
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