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Research Article | Open Access

Variational reconstruction using subdivision surfaces with continuous sharpness control

Beijing Key Lab of Big Data Technology for Food Safety, School of Computer and Information Engineering, Beijing Technology and Business University, China.
College of Engineering, Nanyang Technological University, Singapore.
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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.

Keywords

variational modelsubdivision surfacesharpnesssurface reconstructionL1 norm

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Computational Visual Media
Volume 3 Issue 3,
September 2017
Pages 217-228
DOI: 10.1007/s41095-017-0088-2
Cite this article:
Wu X, Zheng J, Cai Y, et al. Variational reconstruction using subdivision surfaces with continuous sharpness control. Computational Visual Media, 2017, 3(3): 217-228. https://doi.org/10.1007/s41095-017-0088-2

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Revised: 27 February 2017
Accepted: 27 April 2017
Published: 15 June 2017
© The Author(s) 2017

This article is published with open access at Springerlink.com

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