Query-by-sketch image retrieval using data mining for bridging semantic gap
| Project/Area Number |
21700155
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Shizuoka University |
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Principal Investigator |
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2009: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | 知識発見とデータベース / 画像情報処理 / 画像内容検索 / スケッチ画像検索 / 画像特徴量 / オブジェクト抽出 / セマンティック・ギャップ / 部分検索 / 画像認識 / データマイニング / クラスタリング / 適合性フィードバック / クエリー予測 / セマンティックギャップ / データベース |
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| Research Abstract |
The purpose of this study is to bridge the semantic gap between image feature and human subjective using data-mining from huge image data, sketch images and user evaluations and to improve the effectiveness and efficiency of interactive query-by-sketch image retrieval. The query-by-sketch image retrieval using sketch prediction is focused on online stroke. Sketch prediction enables users to obtain target retrieval images without completely finishing input sketch and to bridge the semantic gap.
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Report
(4 results)
Research Products
(36 results)
