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A systematic approach to semantics-based image retrieval and organization using thesaurus 1.
| Content Provider | CiteSeerX |
|---|---|
| Author | Yang, Jun Wenyin, Liu Zhang, Hongjiang Zhuang, Yueting |
| Abstract | Abstract. Semantics-based retrieval capability is greatly desirable for large-scale image collections. This paper proposes a novel approach to semantics-based image retrieval and organization using thesaurus, which addresses the representation, acquisition, and utilization of image semantics in a systematic and integrated manner. Firstly, a semantic network is constructed from thesaurus, which represents the semantic indexes of images using a group of interrelated semantic concepts. A learning strategy is suggested to acquire the semantic indexes from user interactions (including feedbacks) in a progressive and semi-automatic way. Based on the semantic network, a semantic similarity measure is formulated and integrated with visual features to compose an integrated image retrieval algorithm. A set of experiments conducted on real-world images has demonstrated the efficiency and effectiveness of this algorithm compared with existing retrieval algorithms. Furthermore, we propose a method to generate a dynamic image classification that facilitates flexible and convenient user interactions. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Semantics-based Image Retrieval Systematic Approach Organization Using Thesaurus Semantic Network Semantic Index Semantic Concept Integrated Manner Retrieval Algorithm Dynamic Image Classification Integrated Image Retrieval Algorithm Convenient User Interaction Large-scale Image Collection User Interaction Real-world Image Novel Approach Semi-automatic Way Visual Feature Semantics-based Retrieval Capability Semantic Similarity Measure Image Semantics Learning Strategy |
| Content Type | Text |
| Resource Type | Article |
