Variational reconstruction using subdivision surfaces with continuous sharpness control

Abstract We present a variational method for subdivision surface reconstruction from a noisy dense mesh. A new set of subdivision rules with continuous sharpness control is introduced into Loop subdivision for better modeling subdivision surface features such as semi-sharp creases, creases, and corn...

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Main Authors: Xiaoqun Wu, Jianmin Zheng, Yiyu Cai, Haisheng Li
Format: Article
Language:English
Published: SpringerOpen 2017-06-01
Series:Computational Visual Media
Subjects:
Online Access:http://link.springer.com/article/10.1007/s41095-017-0088-2
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spelling doaj-2bff971023f64ea9bf549876aa9251402020-11-24T21:09:56ZengSpringerOpenComputational Visual Media2096-04332096-06622017-06-013321722810.1007/s41095-017-0088-2Variational reconstruction using subdivision surfaces with continuous sharpness controlXiaoqun Wu0Jianmin Zheng1Yiyu Cai2Haisheng Li3Beijing Key Lab of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business UniversityCollege of Engineering, Nanyang Technological UniversityCollege of Engineering, Nanyang Technological UniversityBeijing Key Lab of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business UniversityAbstract We present a variational method for subdivision surface reconstruction from a noisy dense mesh. A new set of subdivision rules with continuous sharpness control is introduced into Loop subdivision for better modeling subdivision surface features such as semi-sharp creases, creases, and corners. The key idea is to assign a sharpness value to each edge of the control mesh to continuously control the surface features. Based on the new subdivision rules, a variational model with L1 norm is formulated to find the control mesh and the corresponding sharpness values of the subdivision surface that best fits the input mesh. An iterative solver based on the augmented Lagrangian method and particle swarm optimization is used to solve the resulting non-linear, non-differentiable optimization problem. Our experimental results show that our method can handle meshes well with sharp/semi-sharp features and noise.http://link.springer.com/article/10.1007/s41095-017-0088-2variational modelsubdivision surfacesharpnesssurface reconstructionL1norm
collection DOAJ
language English
format Article
sources DOAJ
author Xiaoqun Wu
Jianmin Zheng
Yiyu Cai
Haisheng Li
spellingShingle Xiaoqun Wu
Jianmin Zheng
Yiyu Cai
Haisheng Li
Variational reconstruction using subdivision surfaces with continuous sharpness control
Computational Visual Media
variational model
subdivision surface
sharpness
surface reconstruction
L1norm
author_facet Xiaoqun Wu
Jianmin Zheng
Yiyu Cai
Haisheng Li
author_sort Xiaoqun Wu
title Variational reconstruction using subdivision surfaces with continuous sharpness control
title_short Variational reconstruction using subdivision surfaces with continuous sharpness control
title_full Variational reconstruction using subdivision surfaces with continuous sharpness control
title_fullStr Variational reconstruction using subdivision surfaces with continuous sharpness control
title_full_unstemmed Variational reconstruction using subdivision surfaces with continuous sharpness control
title_sort variational reconstruction using subdivision surfaces with continuous sharpness control
publisher SpringerOpen
series Computational Visual Media
issn 2096-0433
2096-0662
publishDate 2017-06-01
description Abstract We present a variational method for subdivision surface reconstruction from a noisy dense mesh. A new set of subdivision rules with continuous sharpness control is introduced into Loop subdivision for better modeling subdivision surface features such as semi-sharp creases, creases, and corners. The key idea is to assign a sharpness value to each edge of the control mesh to continuously control the surface features. Based on the new subdivision rules, a variational model with L1 norm is formulated to find the control mesh and the corresponding sharpness values of the subdivision surface that best fits the input mesh. An iterative solver based on the augmented Lagrangian method and particle swarm optimization is used to solve the resulting non-linear, non-differentiable optimization problem. Our experimental results show that our method can handle meshes well with sharp/semi-sharp features and noise.
topic variational model
subdivision surface
sharpness
surface reconstruction
L1norm
url http://link.springer.com/article/10.1007/s41095-017-0088-2
work_keys_str_mv AT xiaoqunwu variationalreconstructionusingsubdivisionsurfaceswithcontinuoussharpnesscontrol
AT jianminzheng variationalreconstructionusingsubdivisionsurfaceswithcontinuoussharpnesscontrol
AT yiyucai variationalreconstructionusingsubdivisionsurfaceswithcontinuoussharpnesscontrol
AT haishengli variationalreconstructionusingsubdivisionsurfaceswithcontinuoussharpnesscontrol
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