Static and Dynamic Texture Mixing Using Optimal Transport
Static and Dynamic Texture Mixing Using Optimal Transport
复制标题
使用最佳传输的静态和动态纹理混合
DOI：
10.1007/978-3-642-38267-3_12
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
Jean
中科院分区：
文献类型：
--
作者：
Sira Ferradans;Gui;G. Peyré;Jean
本文通过结合图像或视频的输入集的统计特性来处理静态和动态纹理的混合问题。我们专注于遵循静态和高斯模型的斑点噪声纹理，可以从给定的样本中学习。从这里，我们定义，使用最优传输，纹理模型之间的距离，推导出测地线路径，并定义几个纹理模型之间的重心。这些推导是有用的，因为它们允许用户在纹理模型集合内导航，在集合的每个元素处插入新的。从这些新的插值模型，新的纹理可以合成任意大小的空间和时间。从样本库中获得的数值结果表明，我们的方法能够生成新的复杂和逼真的静态和动态纹理。
This paper tackles the problem of mixing static and dynamic texture by combining the statistical properties of an input set of images or videos. We focus on Spot Noise textures that follow a stationary and Gaussian model which can be learned from the given exemplars. From here, we define, using Optimal Transport, the distance between texture models, derive the geodesic path, and define the barycenter between several texture models. These derivations are useful because they allow the user to navigate inside the set of texture models, interpolating a new one at each element of the set. From these new interpolated models, new textures can be synthesized of arbitrary size in space and time. Numerical results obtained from a library of exemplars show the ability of our method to generate new complex and realistic static and dynamic textures.