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An approach to semantics-based image retrieval and browsing *.
| Content Provider | CiteSeerX |
|---|---|
| Author | Yang, Jun Wenyin, Liu Zhang, Hongjiang Zhuang, Yueting |
| Abstract | The state-of-the-art image retrieval approach is to incorporate image semantics with low-level features to enhance retrieval performance. Although many systems annotate images with descriptive keywords and retrieve images by keyword-based search, they have not explored the full potentials of semantics. This paper exploits the power of thesaurus-aided approaches to facilitate semantics-based access to image collections. The contribution of our work includes constructing a dynamic semantic hierarchy (DSH) to support flexible browsing of images by semantic subjects, as well as formulating a semantic similarity metric to improve the accuracy of semantic matching. Both approaches are seamlessly integrated into a unified framework for semantics- and feature-based image retrieval. Experiments conducted on real-world images demonstrate the effectiveness of our approaches. 1. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Approach Semantics-based Image Retrieval Browsing Low-level Feature Many System Annotate Image Semantics-based Access Keyword-based Search State-of-the-art Image Retrieval Approach Semantic Matching Semantic Similarity Semantic Subject Image Collection Full Potential Real-world Image Feature-based Image Retrieval Retrieval Performance Unified Framework Thesaurus-aided Approach Image Semantics Flexible Browsing Dynamic Semantic Hierarchy Descriptive Keywords |
| Content Type | Text |
| Resource Type | Article |
