Polygonization of High-Density and Large-Scale Point Data Based on a Repulsive-Force Particle System on Implicit Surface
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- Kojima Kazuyuki
- Graduate School of Science and Engineering, Ritsumeikan University
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- Oka Masafumi
- Graduate School of Science and Engineering, Ritsumeikan University
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- Shibata Akihiro
- Computing Research Center, High Energy Accelerator Research Organization
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- Nakata Susumu
- College of Information Science and Engineering, Ritsumeikan University
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- Tanaka Satoshi
- College of Information Science and Engineering, Ritsumeikan University
Bibliographic Information
- Other Title
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- 陰関数曲面上における粒子拡散法を用いた高密度・大量点群のポリゴン化
Abstract
For high-quality visualization of a complex implicit surface, we need to decompose it into polygons with high aspect ratio, i.e., polygons that are nearly equilateral triangles. For this purpose, we should realize uniform neighboring distances between sample points generated on the surface. The particle-system method based on interparticle repulsive force is known as an excellent way to realize the uniformity. In the particle- system method, the sample points are regarded as particles for which proper interparticle repulsive force is assigned. Recently, Meyer et al. proposed efficient repulsive force based on a cotangent energy function. For a very high-density, i.e., large-scale particle system, however, their repulsive force becomes ineffective, and the system needs long time to approach an equilibrium state where neighboring-particle distances become uniform. In this paper, we propose a new type of repulsive force that is suitable for high-density particle systems. We show that the proposed repulsive force works well to generate polygons with higher aspect ratio on a target implicit surface, compared with the Mayer et al.'s force. We also show that computation time to make the particle system reach the equilibrium state is shorter.
Journal
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- Transactions of the Visualization Society of Japan
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Transactions of the Visualization Society of Japan 27 (9), 77-83, 2007
The Visualization Society of Japan
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Details 詳細情報について
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- CRID
- 1390282680292598144
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- NII Article ID
- 130004438195
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- ISSN
- 13465260
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed