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Research Article | Open Access

Relief generation from 3D scenes guided by geometric texture richness

Yongwei Miao1,2( ), Yuliang Sun2, Xudong Fang2, Jiazhou Chen2, Xudong Zhang2, Renato Pajarola3
College of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China.
College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China.
Department of Informatics, University of Zürich, Zürich CH-8050, Switzerland.
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Abstract

Typically, relief generation from an input 3D scene is limited to either bas-relief or high-relief modeling. This paper presents a novel unified scheme for synthesizing reliefs guided by the geometric texture richness of 3D scenes; it can generate both bas- and high-reliefs. The type of relief and compression coefficient can be specified according to the user’s artistic needs. We use an energy minimization function to obtain the surface reliefs, which contains a geometry preservation term and an edge constraint term. An edge relief measure determined by geometric texture richness and edge z-depth is utilized to achieve a balance between these two terms. During relief generation, the geometry preservation term keeps local surface detail in the original scenes, while the edge constraint term maintains regions of the original models with rich geometric texture. Elsewhere, in high-reliefs, the edge constraint term also preserves depth discontinuities in the higher parts of the original scenes. The energy function can be discretized to obtain a sparse linear system. The reliefs are obtained by solving it by an iterative process. Finally, we apply non-linear compression to the relief to meet the user’s artistic needs. Experimental results show the method’s effectiveness for generating both bas- and high-reliefs for complex 3D scenes in a unified manner.

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Computational Visual Media
Pages 209-221

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Cite this article:
Miao Y, Sun Y, Fang X, et al. Relief generation from 3D scenes guided by geometric texture richness. Computational Visual Media, 2018, 4(3): 209-221. https://doi.org/10.1007/s41095-018-0111-2

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Revised: 29 December 2017
Accepted: 13 January 2018
Published: 13 March 2018
© The Author(s) 2018

This article is published with open access at Springerlink.com

The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www. editorialmanager.com/cvmj.