Efficiently computing feature-aligned and high-quality polygonal offset surfaces. (February 2018)
- Record Type:
- Journal Article
- Title:
- Efficiently computing feature-aligned and high-quality polygonal offset surfaces. (February 2018)
- Main Title:
- Efficiently computing feature-aligned and high-quality polygonal offset surfaces
- Authors:
- Meng, Wenlong
Chen, Shuangmin
Shu, Zhenyu
Xin, Shi-Qing
Fu, Hongbo
Tu, Changhe - Abstract:
- Highlights: A super-linear convergent algorithm to generate a well-triangulated and feature-aligned offset surface is proposed. We use an optimization method to keep a set of uniformly distributed sites at a specified distance away from the base surface. Our algorithm is suitable for multiple kinds of input surfaces such as triangle meshes, implicit functions, parametric surfaces and even point clouds. Our algorithm has significant advantages in terms of meshing quality, computational performance, topological correctness and feature alignment. Graphical abstract: Abstract: 3D surface offsetting is a fundamental geometric operation in CAD/CAE/CAM. In this paper, we propose a super-linear convergent algorithm to generate a well-triangulated and feature-aligned offset surface based on particle system. The key idea is to distribute a set of moveable sites as uniformly as possible while keeping these sites at a specified distance away from the base surface throughout the optimization process. In order to make the final triangulation align with geometric feature lines, we use the moveable sites to predict the potential feature regions, which in turn guide the distribution of moveable sites. Our algorithm supports multiple kinds of input surfaces, e.g., triangle meshes, implicit functions, parametric surfaces and even point clouds. Compared with existing algorithms on surface offsetting, our algorithm has significant advantages in terms of meshing quality, computationalHighlights: A super-linear convergent algorithm to generate a well-triangulated and feature-aligned offset surface is proposed. We use an optimization method to keep a set of uniformly distributed sites at a specified distance away from the base surface. Our algorithm is suitable for multiple kinds of input surfaces such as triangle meshes, implicit functions, parametric surfaces and even point clouds. Our algorithm has significant advantages in terms of meshing quality, computational performance, topological correctness and feature alignment. Graphical abstract: Abstract: 3D surface offsetting is a fundamental geometric operation in CAD/CAE/CAM. In this paper, we propose a super-linear convergent algorithm to generate a well-triangulated and feature-aligned offset surface based on particle system. The key idea is to distribute a set of moveable sites as uniformly as possible while keeping these sites at a specified distance away from the base surface throughout the optimization process. In order to make the final triangulation align with geometric feature lines, we use the moveable sites to predict the potential feature regions, which in turn guide the distribution of moveable sites. Our algorithm supports multiple kinds of input surfaces, e.g., triangle meshes, implicit functions, parametric surfaces and even point clouds. Compared with existing algorithms on surface offsetting, our algorithm has significant advantages in terms of meshing quality, computational performance, topological correctness and feature alignment. … (more)
- Is Part Of:
- Computers & graphics. Volume 70(2018)
- Journal:
- Computers & graphics
- Issue:
- Volume 70(2018)
- Issue Display:
- Volume 70, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 70
- Issue:
- 2018
- Issue Sort Value:
- 2018-0070-2018-0000
- Page Start:
- 62
- Page End:
- 70
- Publication Date:
- 2018-02
- Subjects:
- Offsetting -- Particle system -- Feature alignment
Computer graphics -- Periodicals
006.6 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.cag.2017.07.003 ↗
- Languages:
- English
- ISSNs:
- 0097-8493
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.700000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11345.xml