| Project/Area Number |
10044174
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| Research Category |
Grant-in-Aid for Scientific Research (B).
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Engineering fundamentals
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| Research Institution | Chuo University |
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Principal Investigator |
IMAI Keiko Chuo University, Faculty of Sci.and Eng., Prof., 理工学部, 教授 (70203289)
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| Co-Investigator(Kenkyū-buntansha) |
INABA Mary Univ.Tokyo, Graduate School of Science, Lecturer, 大学院・理学系研究科, 講師 (60282711)
IMAI Hiroshi Univ.Tokyo, Graduate School of Sci., Assoc.Prof., 大学院・理学系研究科, 助教授 (80183010)
ASANO Takao Chuo University, Faculty of Sci.and Eng., Prof., 理工学部, 教授 (90124544)
ONISHI Kensuke Univ.Electro-Communications, Assoc.Researcher, 大学院・情報システム研究科, 助手 (00303024)
AVIS David McGill大学, 情報工学科, 教授
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| Project Period (FY) |
1998 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥5,600,000 (Direct Cost: ¥5,600,000)
Fiscal Year 2000: ¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 1999: ¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 1998: ¥2,200,000 (Direct Cost: ¥2,200,000)
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| Keywords | discrete geometry / computational geometry / geographical information system / Voronoi diagram / triangulation / convex polytope / geographical database / 地理データベース / クラスタリング / 点位置決定問題 / 計算幾何 / 離散幾何 / 配送計画 / 3角形分割 / マルチメディア探索 / 列挙と数え上げ |
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| Research Abstract |
It is very important to process geometric information at high speed by computers in the multimedia era. The aim of this joint research is to develop efficient algorithms for discrete and computational geometry. Voronoi diagrams, triangulations, convex polytopes are basic concepts, and many problems which appear in applications can be solved by those concepts. From the theoretical viewpoint, we study mathematical and algorithmic research for triangulations and convex polytopes.
In multimedia era, geographical information systems (GIS for short) have been investigated and we have to solve many problems with geometric information in GIS.The Voronoi diagram has been used directly in GIS, and we generalize it to the diagram in statistical parameter space. When GIS is combined with other data such as population data, the space becomes higher-dimensional geometric space, to which our generalized diagrams can be used to find proximity relations, etc., by using computational-geometric algorithms. We also developed efficient geometric clustering algorithms, both in Euclidean and information geometric spaces, and applied them to geographical data mining. Also, map labeling problem and point location problems are studied. Concerning the map labeling problem, subway maps are intensively studied where labels corresponding to each subway line are automatically placed in a beautiful way.
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