Visual Event Learning with Web Resources
| Project/Area Number |
26540081
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Perceptual information processing
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| Research Institution | Nagoya University |
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Principal Investigator |
KATO Jien 名古屋大学, 情報科学研究科, 准教授 (70251882)
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| Project Period (FY) |
2014-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | イベント認識 / 行動認識 / 学習データ収集の省力化 / 適応学習 / 近似スパースコーディング / 画像・映像検索 / 特徴次元選択 / データ選択 / パッチワイズ学習 / クロスデータセット / セルフトレニング / 適応型距離マトリック学習 |
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| Outline of Final Research Achievements |
The objective of this research is to develop a low cost event learning framework to enable easy event learning and recognition. The proposed framework has the following three components: (1) web data collecting, which helps to prepare learning data efficiently; (2) robust event learning, which guarantees the event recognition performance; and (3) domain adaption, which helps to transform the event models learned from the web domain to the target domain. In our work, we developed (1) a flexible event retrieval approach by integrating image recognition and nature language processing; (2) an approximate sparse coding based high performance event recognition approach; and (3) a feature selection based domain transform approach for adapting event model between different domains. The proposed objectives of this research have been mostly achieved.
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Report
(3 results)
Research Products
(16 results)
