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High-quality tree structures modelling using local convolution surface approximation

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Abstract

In this paper, we propose a local convolution surface approximation approach for quickly modelling tree structures with pleasing visual effect. Using our proposed local convolution surface approximation, we present a tree modelling scheme to create the structure of a tree with a single high-quality quad-only mesh. Through combining the strengths of the convolution surfaces, subdivision surfaces and GPU, our tree modelling approach achieves high efficiency and good mesh quality. With our method, we first extract the line skeletons of given tree models by contracting the meshes with the Laplace operator. Then we approximate the original tree mesh with a convolution surface based on the extracted skeletons. Next, we tessellate the tree trunks represented by convolution surfaces into quad-only subdivision surfaces with good edge flow along the skeletal directions. We implement the most time-consuming subdivision and convolution approximation on the GPU with CUDA, and demonstrate applications of our proposed approach in branch editing and tree composition.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant Nos. 61272298 and 61373084), Zhejiang Provincial Natural Science Foundation of China (Grant No. Z1110154), the China 863 program (Grant Nos. 2012AA011503 and 2013AA01A603), and the Major Science and Technology Innovation Team (Grant no. 2010R50040).

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Authors and Affiliations

  1. State Key Lab of CAD&CG, Zhejiang University, Hangzhou, 310058, People’s Republic of China

    Xiaoqiang Zhu & Xiaogang Jin

  2. School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, People’s Republic of China

    Xiaoqiang Zhu

  3. National Center for Computer Animation, Bournemouth University, Bournemouth, UK

    Lihua You

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  1. Xiaoqiang Zhu
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Correspondence to Xiaogang Jin.

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Zhu, X., Jin, X. & You, L. High-quality tree structures modelling using local convolution surface approximation. Vis Comput 31, 69–82 (2015). https://doi.org/10.1007/s00371-013-0905-2

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