Semantic Approach to Image Database Classification and Retrieval
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概要
- 論文の詳細を見る
This paper demonstrates an approach to image retrieval founded on classifying image regions hierarchically based on their semantics (e.g., sky, snow, rocks, etc.) that resemble peoples' perception rather than on low-level features (e.g., color, texture, shape, etc.). Particularly, we consider to automatically classify regions of outdoor images based on their semantics using the support vector machines (SVMs) tool. First, image regions are segmented using the hill-climbing method. Then, those regions are classified by the SVMs. The SVMs learn the semantics of specified classes from a test database of image regions. Such semantic classification allows the implementation of intuitive query interface. As we show in our experiments, the high precision of semantic classification justifies the feasibility of our approach.
- 国立情報学研究所の論文
- 2003-09-30
著者
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Makinouchi Akifumi
Graduate School of Information Science and Electrical Engineering, Department of Intelligent Systems
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Aghbari Z
Graduate School Of Information Science And E.e. Kyushu University
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Aghbari Zaher
Graduate School Of Information Science And Electrical Engineering Department Of Intelligent Systems
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Aghbari Zaher
Graduate School Of Information Science And Electrical Engineering Department Of Intelligent System K
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Makinouchi Akifumi
Graduate School Of Information Science And E.e. Kyushu University
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AGHBARI Zaher
Graduate School of Information Science and E.E., Kyushu University
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