| Project/Area Number |
11680349
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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 Faculty of Science, Ochanomizu University, Professor, 理学部, 教授 (00181347)
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| Co-Investigator(Kenkyū-buntansha) |
TAKESHIMA Yuriko Graduate School of Humanities and Sciences, Ochanomizu University, Research associate, 大学院・人間文化研究科, 助手 (20313398)
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| Project Period (FY) |
1999 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2000: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 1999: ¥2,300,000 (Direct Cost: ¥2,300,000)
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| Keywords | Scientific visualization / volume visualization / volume rendering / isosurface / differential topology / transfer function / singular point / Reeb graph / 色相 / 不透明度 / 半自動設計 / データマイニング / ホモトピー |
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| Research Abstract |
Volume visualization has served as an indispensable methodology in various disciplines for exploring the inner structures and complex behavior of volumetric objects embedded in large-scale sampled or simulated 3D datasets. Although the advent of hardware-based acceleration mechanisms enables the user to visualize such volumes interactively, the rapid increase in their data size makes it difficult to adjust transfer functions sufficiently with repeated evaluation of resulting images. In this study, we take advantage of a 3D field topology analysis to optimize the transfer functions aiming at volume data mining. The conventional Reeb graph-based approach to describing the topological features of 3D surfaces is extended to capture the topological skeleton of a volumetric field. Based on the analysis results, which are represented in the form of hyper Reeb graphs, we proposed two principles to design appropriate color/opacity transfer functions for direct volume rendering. A feasibility study of the proposed methodology is performed with analytic trivariate functions, a large-scale 4D simulated dataset from atomic collision research, and a CT scanned tooth dataset.
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