| Project/Area Number |
15500100
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | TOKYO INSTITUTE OF TECHNOLOGY |
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Principal Investigator |
KUMAZAWA Itsuo Tokyo Institute of Technology, Imaging Science and Engineering Laboratory, Professor, 大学院・理工学研究科, 教授 (70186469)
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| Project Period (FY) |
2003 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2004: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2003: ¥2,600,000 (Direct Cost: ¥2,600,000)
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| Keywords | Three dimensional shape modeling / Multiple view images / Neural Network / Distance measurement / Stereo Matching / Learning algorithm / Infra red distance sensor / three dimensional graphics / 3次元形状モデリング / 赤外線 / 3次元映像コンテンツ / Shape from Shading / 照明条件 / Simulated Annealing / 勾配法 / 誤差逆伝搬法 |
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| Research Abstract |
Novel Artificial Neural Networks were developed for automatic modeling of three dimensional shapes. These neural networks have capabilities of learning a function of modeling three dimensional shapes from their multiple view images. To model the shapes, they use a polyhedron, models represented by the special architecture of the network and connection weights among the network. These connection weights are updated during the learning process by using multiple view images so that the views of the polyhedron models coincide with the corresponding views of the actual shapes. The performance of the proposed methods is evaluated by some experiments. By combining multiple view images in addition to other distance information measured, by infra red illumination method, the method gave improve results with robustness against noises and errors. Stereo matching based distance measurement method is also jointly applied to the method and contradicting results were fixed by error correction procedure.
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