| Project/Area Number |
13680401
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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 |
計算機科学
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| Research Institution | Ochanomizu University |
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Principal Investigator |
FUJISHIRO Issei Ochanomizu University, Graduate School of Humanities and Sciences, Professor, 大学院・人間文化研究所, 教授 (00181347)
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| Co-Investigator(Kenkyū-buntansha) |
TAKESHIMA Yuriko Tohoku University, Institute of Fluid Science, Research associate, 流体科学研究所, 助手 (20313398)
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| Project Period (FY) |
2001 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥4,100,000 (Direct Cost: ¥4,100,000)
Fiscal Year 2002: ¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 2001: ¥2,400,000 (Direct Cost: ¥2,400,000)
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| Keywords | visual data mining / topology / line integral convolution / volume rendering / transfer function / Line Integral Convolution / データマイグレーション / データマイニング / 特異点理論 / フロートポロジー / 重要度マップ / フロービジュアリゼーション |
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| Research Abstract |
In this research, a texture-based vector visualization method, called LIC (Line Integral Convolution), has been extended to three-dimensional fields. A sophisticated vector volume visualization code has been developed, which can adaptively visualize inner structures of interest around critical points within generated 3D LIC textures by topologically-accentuated spatial transfer functions and a 3D streamline illumination model.
The core algorithm consists of the following four steps :
1) Generate a 3D volume for solid LIC texture from a given vector field by using a method developed by Mao, et al (1997).
2) Locate critical points of the field with differential topology methods.
3) Accentuate spatial transfer functions in a topological manner so that they can reflect the significance distribution analyzed in Step 2.
4) Volume render the LIC volume generated in Step 1 with the spatial transfer functions and a 3D streamline illumination model.
The above method has been implemented on a GPU-enhanced volume graphics PC and cluster systems for providing a real-time volume data mining environment. The effectiveness of the tool has been proved empirically with an application to several practical datasets, including a simulated tornado dataset provided by R. Crawfis of Ohio State University, US, and geo-scientific datasets generated by using GeoFEM, known as a parallel FEM middleware for the Earth Simulator.
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