Semi‐Procedural Textures Using Point Process Texture Basis Functions
Semi‐Procedural Textures Using Point Process Texture Basis Functions
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DOI：
10.1111/cgf.14061
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发表时间：
2020-07
影响因子：
2.5
通讯作者：
Pascal Guehl;Rémi Allègre;J. Dischler;Bedrich Benes;Eric Galin
中科院分区：
文献类型：
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作者：
Pascal Guehl;Rémi Allègre;J. Dischler;Bedrich Benes;Eric Galin
我们引入了一种新的半过程方法，避免了过程纹理的缺点，并利用数据驱动的纹理合成的优势。我们将合成分为两部分：1）基于程序参数模型的结构合成和2）数据驱动的颜色细节合成。程序模型由通用点过程纹理基函数（PPTBF）组成，它通过定义丰富的卷积核来扩展稀疏卷积噪声。它们由一个窗口函数乘以一个相关的统计混合的Gabor函数，两者都旨在封装一个大跨度的常见的空间随机结构，包括细胞，裂缝，颗粒，划痕，斑点，污渍和波。通过提供二进制结构范例，可以自动指定参数。至于基于噪声的高斯纹理，PPTBF用作独立函数，避免了处理多个程序资产时发生的分类任务。由于PPTBF是基于一组参数，它允许不同的视觉结构之间的连续过渡和容易控制其视觉特性。颜色是一致的合成从样本使用多尺度并行纹理合成的数字，PPTBF的约束。生成的纹理是参数化的，无限的，避免重复。数据驱动部分是自动的，并保证与输入的视觉相似性。
We introduce a novel semi‐procedural approach that avoids drawbacks of procedural textures and leverages advantages of data‐driven texture synthesis. We split synthesis in two parts: 1) structure synthesis, based on a procedural parametric model and 2) color details synthesis, being data‐driven. The procedural model consists of a generic Point Process Texture Basis Function (PPTBF), which extends sparse convolution noises by defining rich convolution kernels. They consist of a window function multiplied with a correlated statistical mixture of Gabor functions, both designed to encapsulate a large span of common spatial stochastic structures, including cells, cracks, grains, scratches, spots, stains, and waves. Parameters can be prescribed automatically by supplying binary structure exemplars. As for noise‐based Gaussian textures, the PPTBF is used as stand‐alone function, avoiding classification tasks that occur when handling multiple procedural assets. Because the PPTBF is based on a single set of parameters it allows for continuous transitions between different visual structures and an easy control over its visual characteristics. Color is consistently synthesized from the exemplar using a multiscale parallel texture synthesis by numbers, constrained by the PPTBF. The generated textures are parametric, infinite and avoid repetition. The data‐driven part is automatic and guarantees strong visual resemblance with inputs.