Metric first reconstruction for interactive curvature-aware modeling. (September 2020)
- Record Type:
- Journal Article
- Title:
- Metric first reconstruction for interactive curvature-aware modeling. (September 2020)
- Main Title:
- Metric first reconstruction for interactive curvature-aware modeling
- Authors:
- Fang, Qing
Zhao, Zheng-Yu
Liu, Zhong-Yuan
Liu, Ligang
Fu, Xiao-Ming - Abstract:
- Abstract: We present a novel curvature-aware modeling technique for interactively designing shapes. The basic principle we used is that an intrinsic metric of a mesh determines the Euclidean edge lengths and the angles, thereby defining the Laplacian matrix. Hence central to our approach is a metric first algorithm that interactively reconstructs a shape for matching the prescribed curvatures. Given Gaussian curvature, the Calabi flow, which implies a conformal deformation, is first used to compute the desired intrinsic metric. We accelerate the convergence of the Calabi flow using a progressive strategy. Then we reconstruct a shape by solving a new unconstrained problem to match the target Euclidean edge lengths defined by the computed metric and the input mean curvature computed by the Laplacian matrix. Since the obtained metric makes the target edge lengths and the Laplacian matrix fixed during the optimization, we can easily apply a local–global solver capable of interactively reconstructing shapes. Based on this reconstruction tool, we develop three curvature-aware modeling operations. A large number of experiments demonstrate the capability and feasibility of our method for interactively modeling complex shapes. Highlights: Curvature-aware modeling technique given target Gaussian and mean curvature. Metric first algorithm using a modified local–global solver. An interface tool for designing shapes in the interactive speeds. Easily cartoonizing existing models withoutAbstract: We present a novel curvature-aware modeling technique for interactively designing shapes. The basic principle we used is that an intrinsic metric of a mesh determines the Euclidean edge lengths and the angles, thereby defining the Laplacian matrix. Hence central to our approach is a metric first algorithm that interactively reconstructs a shape for matching the prescribed curvatures. Given Gaussian curvature, the Calabi flow, which implies a conformal deformation, is first used to compute the desired intrinsic metric. We accelerate the convergence of the Calabi flow using a progressive strategy. Then we reconstruct a shape by solving a new unconstrained problem to match the target Euclidean edge lengths defined by the computed metric and the input mean curvature computed by the Laplacian matrix. Since the obtained metric makes the target edge lengths and the Laplacian matrix fixed during the optimization, we can easily apply a local–global solver capable of interactively reconstructing shapes. Based on this reconstruction tool, we develop three curvature-aware modeling operations. A large number of experiments demonstrate the capability and feasibility of our method for interactively modeling complex shapes. Highlights: Curvature-aware modeling technique given target Gaussian and mean curvature. Metric first algorithm using a modified local–global solver. An interface tool for designing shapes in the interactive speeds. Easily cartoonizing existing models without complicated operations. … (more)
- Is Part Of:
- Computer aided design. Volume 126(2020)
- Journal:
- Computer aided design
- Issue:
- Volume 126(2020)
- Issue Display:
- Volume 126, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 126
- Issue:
- 2020
- Issue Sort Value:
- 2020-0126-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09
- Subjects:
- Curvature-aware reconstruction -- Interactive modeling and processing -- Calabi flow -- Local–global optimization
Computer-aided design -- Periodicals
Engineering design -- Data processing -- Periodicals
Computer graphics -- Periodicals
Conception technique -- Informatique -- Périodiques
Infographie -- Périodiques
Computer graphics
Engineering design -- Data processing
Periodicals
Electronic journals
620.00420285 - Journal URLs:
- http://www.journals.elsevier.com/computer-aided-design/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cad.2020.102863 ↗
- Languages:
- English
- ISSNs:
- 0010-4485
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3393.520000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 13489.xml