| Project/Area Number |
06452396
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | University of Tsukuba |
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Principal Investigator |
OHTA Yuichi Univ.of Tsukuba, Inst.of Inf.Sci., Professor, 電子・情報工学系, 教授 (50115804)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAMURA Yuichi Univ.of Tsukuba, Inst.of Inf.Sci., Assistant Professor, 電子・情報工学系, 講師 (40227947)
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| Project Period (FY) |
1994 – 1995
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| Project Status |
Completed (Fiscal Year 1995)
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| Budget Amount *help |
¥5,500,000 (Direct Cost: ¥5,500,000)
Fiscal Year 1995: ¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 1994: ¥3,800,000 (Direct Cost: ¥3,800,000)
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| Keywords | Video Indexing / Gesture Dialog Relation / Human Behavior Understanding / Image Understanding / Media Integration / Natural Language Processing / Human Interface / Presentation / 画像認識 / プレゼンテーションの理解 / 動画像処理 / ジェスチャー認識 / 自然言語とパターン情報の統合 |
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| Research Abstract |
In the understanding of human behaviors, there is a lot of ambiguities which depend on the situation. It is because few strict laws or rules are applicable throughout a wide variety of situations. We have examined the relationship between the gestures and the context of situation which typically represented in the spoken dialog. We proposed a novel framework to understand the behaviro in oral presentations.
1. Human behavior understanding in oral presentation : We developed a method to extract visual keys from presentation images. We also developed a method to extract linguistic keys from spoken words in the presentation. A novel framework was developed to integrate the both keys to resolve the intention of the presenter.
2. Temporal structure analysis of video by image and sound processing : We have developed a method to estimate the temporal structure of a video sequence considering the contents and the intention of the author. it uses the visual and sound keys. Television commercials are used as the target presentation images.
3. Knowledge extraction from diagram and text : We developed a new framework for knowledge extraction from written texts and diagrams and utilization of the obtained knowledge for the automatic organization of flexible hyper-media.
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