2018 Fiscal Year Final Research Report
High-fidelity Photometric 3D Imaging and its Applications
| Project/Area Number |
16H01732
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perceptual information processing
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| Research Institution | Osaka University |
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Principal Investigator |
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| Research Collaborator |
TAGAWA SEIICHI
YAGI YASUSHI
IKEUCHI KATSUSHI
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Keywords | コンピュータビジョン / ３次元形状推定 |
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| Outline of Final Research Achievements |
3D imaging of real-world objects using a camera is a central problem in computer vision due to its wide application areas such as robot control, object recognition by machines, autonomous driving, and product inspection. It has been understood that 3D imaging with ``photometric'' information enables high-fidelity acquisition of 3D shape. In this work, we advance the photometric 3D imaging technology with an emphasis on enabling (a) 3D measurement of surfaces with diverse reflectances, and (b) an easy-to-use imaging setup. As a result, we have developed a thread of new photometric 3D imaging technologies and achieved the intended goals.
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| Free Research Field |
コンピュータビジョン
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| Academic Significance and Societal Importance of the Research Achievements |
研究成果の学術的意義は大きく２点ある．一つは，これまで必須と考えられてきた光源強度のキャリブレーションが不要であることを理論的に示し，新たな照度差ステレオ技術を提案した(semi-calibrated photometric stereo)．この結果により，実際のアプリケーションにおいてもキャリブレーションの手間が緩和できることがわかった．二つ目は，機械学習と光学的３次元イメージングの方向性を打ち出したことである．具体的には深層学習を用いてこれまで困難であった反射特性のモデリングをバイパスし，見えと形状のマッピング関数を学習させるというアプローチ世界に先駆けて提案した．
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