Context based Gesture Modeling based on Interaction Data Mining
| Project/Area Number |
22700146
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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 | Tokyo Institute of Technology (2011-2012)
Kyoto University (2010) |
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Principal Investigator |
OKADA Shogo 東京工業大学, 大学院・総合理工学研究科, 助教 (00512261)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2012: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2011: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2010: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 知識発見とデータマイニング / マルチモーダルパターン認識モデル / 多人数インタラクション / 社会情報学 / パターン認識 / 機械学習 / ジェスチャ認識 / マルチモーダル / データマイニング / 時系列解析 / 知能情報処理 |
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| Research Abstract |
This research proposed a conversation context based gesture recognition approach.In this research, we extract features of co-occurring nonverbal patterns with gestures, i.e., speech act, head gesture, and head direction of each participant, by using pattern recognition techniques. In the experiments, we collect eight group narrative interaction datasets to evaluate the classification performance. The experimental results show that gesture phase features and nonverbal features of other participants improves the performance to discriminate communicative gestures that are used in narrative speeches and other gestures from 20 %
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Report
(4 results)
Research Products
(50 results)
