| Project/Area Number |
16K00707
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Design science
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| Research Institution | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | デザイン設計支援 / 拡張現実感 / 景観 / シミュレーション / 複合現実感 / 環境推定 / 緑視率 / 深層学習 / 天空率 / 隠消現実感 / アルゴリズム / Structure from Motion / 設計工学 / 環境質定量化・予測 / 可視化 / 環境調和型都市基盤整備・建築 / シミュレーション工学 |
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| Outline of Final Research Achievements |
In this research, an AR (Augmented Reality) system for architectural and urban field was developed which consists of estimation functions of the current environment in addition to overlaying 3D virtual model on live video via the same viewpoint. To realize this challenge, an automatic estimation of green view index, and an optical integrity and occlusion processing between 3D virtual model and live video were implemented using image processing and deep learning technology. After prototype systems have been applied virtual projects in Osaka University Campus, were confirmed the applicability of the system.
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| Academic Significance and Societal Importance of the Research Achievements |
建築・都市分野では，設計対象など現存しない3次元空間や，視野に含まれる緑の量など視認が困難な対象が含まれる．本研究は，これら肉眼では見えない情報を，より高精度・高機能な状態で実現可能なAR（拡張現実）システムを開発したものである．ARは，ユーザーがAR体験している現実空間とつながりを保ちながら，見えない情報を現実空間に重ね合わせることができるため，設計対象地や建設現場などの現実空間で，高い臨場感の中で建築・都市の検討が可能となる．
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