| Project/Area Number |
25540045
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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 |
High performance computing
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| Research Institution | Keio University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
MAO Xiaoyang 山梨大学, 総合研究部, 教授 (20283195)
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| Project Period (FY) |
2013-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2014: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2013: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 環境可視化 / ビッグデータ / 半構造映像データ / 抽象化階層 / 人称変換 / 深度付カメラ / 裸眼立体視 / 情動 / パブリックディスプレイ / ジェスチャ認識 / 機械学習 |
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| Outline of Final Research Achievements |
In this study, a rapid prototyping was conducted to develop an ambient visualization system towards the big data era. We focused our attention to semi-structured information embedded in a set of imagery datasets produced routinely, to convert its abstraction hierarchy to the corresponding nested layered graph. Then we employed a depth camera to keep track of the gaze and gesture of a viewer to detect changes in his/her affect in an unconscious way, in order to make it possible to adaptively transform his/her person view through the up-and-down movement over the layers in the abstraction hierarchy. By taking full advantage of this hierarchical browsing together with simple naked-eye stereovision functions, a strong support can be provided for audience in front of digital signage or through SNS to comprehend a given universe of discourse wholly for subsequent prompt and effective actions.
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