| Project/Area Number |
10558053
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| Research Category |
Grant-in-Aid for Scientific Research (B).
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
情報システム学(含情報図書館学)
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| Research Institution | Nagoya University |
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Principal Investigator |
WATANABE Toyohide Graduate School of Engineering, Department of Information Engineering, Nagoya University, Professor, 大学院・工学研究科, 教授 (80093342)
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| Co-Investigator(Kenkyū-buntansha) |
USHIAMA Taketoshi Kyushu Institute of Design, Department of Art and Information Design, Research Associate, 芸術工学部, 助手 (50315157)
ASAKURA Koichi Graduate School of Engineering, Department of Information Engineering, Nagoya University, Research Associate, 大学院・工学研究科, 助手 (80273283)
KATO Jien Graduate School of Engineering, Department of Information Engineering, Nagoya University, Associate Professor, 大学院・工学研究科, 助教授 (70251882)
佐川 雄二 名古屋大学, 工学研究科, 講師 (90242833)
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| Project Period (FY) |
1998 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥12,200,000 (Direct Cost: ¥12,200,000)
Fiscal Year 2000: ¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1999: ¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 1998: ¥6,300,000 (Direct Cost: ¥6,300,000)
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| Keywords | Video Databases / Video of Baseball Games / Automaton / Event / Activity / Browsing / Content Retrieval / Similar-Scenes Retrieval / ハイパービデオ / 類似検索 / 確率モデル / 意味表現 / 概念階層 / 野球録画データ / マルチメディア・データベース / イベント系列 / シーン検索 / ダイジェスト生成 / インデックス系列 / ビデオ・スキーマ / 利用者の視点 |
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| Research Abstract |
Concerning the subject about the construction of video databases, we developed the event-activity model.The events are defined as the features of objects observed from the difference among frames and also the activities are composed as a sequence of continuously ordered events. Additionally, we implemented the prototyping system STRIKE for managing video databases, based on such a model. In many of the traditional approaches, the retrieval facilities are dependent on the indexes for scenes with several frames, and identify only the preset scenes. On the other hand, the indexes in our approach are assigned to individual characteristic frames as events and the retrieval facilities can select various scenes which match with a sequence of events adaptively. Namely, the retrieval facility looks upon the retrieval conditions as activities for patterns of a sequence of events, and a sequence of events to be consistent with the event pattern from video frames. The automaton which supports the retrieval facility basically transfers its own internal state to the acceptable state in accordance with the order of input events, and identifies scenes, corresponded by activities effectively.
Our research subject was scheduled during 3 years until 2000, and contributed the following mechanism and functions for managing video databases :
- scene retrieval through a sequence of events ;
- content-based retrieval controlled by automaton mechanism ;
- automatic indexing to video frames ;
- user-oriented retrieval, based on semantic roles among events/objects ;
- similar scene retrieval ;
- automatic composition of digests for topic scenes ;
- hyper-video for effective browsing.
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