论文标题
高斯曲率滤波器上的3D网眼
Gaussian Curvature Filter on 3D Meshes
论文作者
论文摘要
最大程度地减少网格的高斯曲率可以在3D网格加工中发挥基本作用。但是，缺乏计算高效且坚固的高斯曲率优化方法。在本文中，我们提出了一种简单而有效的方法，可以有效地减少3D网格的高斯曲率。我们首先介绍我们方法的数学基础。然后，我们引入了一种名为高斯曲率滤波器（GCF）的简单且坚固的隐式高斯曲率优化方法。 GCF隐式最小化高斯曲率，而无需明确计算高斯曲率本身。 GCF高效，该方法可用于涉及高斯曲率的大量应用中。我们进行了广泛的实验，以证明GCF在最小化高斯曲率和几何特征方面显着胜过最先进的方法，并在3D网格上保持舒缓。 GCF程序可在https://github.com/tangwenming/gcf-filter上获得。
Minimizing the Gaussian curvature of meshes can play a fundamental role in 3D mesh processing. However, there is a lack of computationally efficient and robust Gaussian curvature optimization method. In this paper, we present a simple yet effective method that can efficiently reduce Gaussian curvature for 3D meshes. We first present the mathematical foundation of our method. Then, we introduce a simple and robust implicit Gaussian curvature optimization method named Gaussian Curvature Filter (GCF). GCF implicitly minimizes Gaussian curvature without the need to explicitly calculate the Gaussian curvature itself. GCF is highly efficient and this method can be used in a large range of applications that involve Gaussian curvature. We conduct extensive experiments to demonstrate that GCF significantly outperforms state-of-the-art methods in minimizing Gaussian curvature, and geometric feature preserving soothing on 3D meshes. GCF program is available at https://github.com/tangwenming/GCF-filter.
