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Vector solid texture synthesis using unified RBF-based representation and optimization

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Abstract

Solid textures are essential for modeling virtual internal materials. Existing approaches either generate raster solid textures or only focus on vector representation. To facilitate efficient synthesis and intuitive editing of vector solid texture, we propose the novel solid texture representation, named radial basis function (RBF) solid texture. An RBF solid texture consists of a set of spatially distributed RBF instances. Each RBF instance encapsulates a 3D position, an RGB color and a signed distance field (SDF) value. Such a representation is resolution independent, compact in storage and capable of supporting efficient random access with an indexing uniform grid. We directly synthesize RBF solid texture from raster exemplar by minimizing an energy function, which encodes the position, color and SDF difference between output volumetric RBF instances and input example planar RBF instances. The minimization process iteratively updates output RBF instances with an EM algorithm. Our experiments show that our algorithm can produce RBF solid textures in high efficiency and compact storage for a variety of exemplars, including stochastic patterns or more structured patterns. Furthermore, RBF solid textures we proposed benefit intuitive editing for either region-based and RBF-based effects.

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Acknowledgements

This work was supported by Key-Area Research and Development Program of Guangdong Province, China (2019B010149002, 2020B010165004), National Natural Science Foundation of China (62072452, 61802386), Natural Science Foundation of Guangdong Province (2020A1515010357, 2021A1515011869), Shenzhen Science and Technology Program (Nos. JCYJ20200109115627045, JCYJ20200109114233670, JCYJ20180507182410327).

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Authors and Affiliations

  1. Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yinling Qian & Qiong Wang

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Jian Shi

  3. University of Electronic Science and Technology of China, Chengdu, China

    Hanqiu Sun

  4. Institute of Software, Chinese Academy of Sciences, Beijing, China

    Yanyun Chen

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  1. Yinling Qian
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Qian, Y., Shi, J., Sun, H. et al. Vector solid texture synthesis using unified RBF-based representation and optimization. Vis Comput 39, 3963–3977 (2023). https://doi.org/10.1007/s00371-022-02541-y

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