| Project/Area Number |
17K13571
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Archaeology
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| Research Institution | Osaka Institute of Technology |
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Principal Investigator |
Muraki Yuta 大阪工業大学, 情報科学部, 講師 (60710077)
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 三次元計測 / デジタルアーカイブ / 位置合わせ / 欠損検出 / 欠損補間 / 機械学習 / 点群 / 3次元計測 / テクスチャ補間 / ディジタルアーカイブ |
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| Outline of Final Research Achievements |
In this research, we have developed a system for advanced defect detection, advanced defect interpolation, texture interpolation using machine learning, and 3D shape generation for measurement points. In defect detection and interpolation, a highly accurate method was established by dynamically determining the evaluation value and the weight from the information around the defect. We also worked on 3D shape generation using machine learning, and conducted verification and generation experiments on effective learning data. Furthermore, we also examined the exhibition method by displaying the three-dimensional shape generated by this research on a normal display or a head-mounted display such as VR or MR.
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| Academic Significance and Societal Importance of the Research Achievements |
本システムは，高速かつ高精度な点群処理技術であることに加え，遺物のデジタルアーカイブ化のボトルネックとなるユーザ負担を低減するといった特色がある．これまでユーザが手動で決定していたパラメータを，コンピュータ側で自動決定する仕組みを提案しており，遺物のデジタルアーカイブ化の更なる促進が予想される．また，提案する機械学習を用いた3次元形状生成手法を用いることで，大きな欠損領域に対する補間手法へと応用が期待できる．
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