基于形状控制的细分曲面的局部渐进插值方法

提出一种基于形状控制的 Catmull-Clark 细分曲面构造方法,实现局部插值任意拓扑的四边形网格顶点。首先该方法利用渐进迭代逼近方法的局部性质,在初始网格中选取若干控制顶点进行迭代调整,保持其他顶点不变,使得最终生成的极限细分曲面插值于初始网格中的被调整点;其次该方法的 Catmull-Clark 细分的形状控制建立在两步细分的基础上,第一步通过对初始网格应用改造的 Catmull-Clark 细分产生新的网格,第二步对新网格应用 Catmull-Clark 细分生成极限曲面,改造的 Catmull-Clark 细分为每个网格面加入参数值,这些参数值为控制局部插值曲面的形状提供了自由度。证明了基于形状控制的 Catmull-Clark 细分局部渐进插值方法的收敛性。实验结果验证了该方法可同时实现局部插值和形状控制。     

形状可调的Loop 细分曲面渐进插值方法

针对Loop 细分无法调整形状与不能插值的问题,提出了一种形状可调的Loop 细分 曲面渐进插值方法。首先给出了一个既能对细分网格顶点统一调整又便于引入权因子实现细分曲 面形状可调的等价Loop 细分模板。其次,通过渐进迭代调整初始控制网格顶点生成新网格,运 用本文的两步Loop 细分方法对新网格进行细分,得到插值于初始控制顶点的形状可调的Loop 细分曲面。最后,证明了该方法的收敛性,并给出实例验证了该方法的有效性。     

基于顶点法向量约束的Catmull-Clark细分插值方法

提出一种基于顶点法向量约束实现插值的两步Catmull-Clark细分方法.第一步,通过改造型Catmull-Clark细分生成新网格.第二步,通过顶点法向量约束对新网格进行调整.两步细分分别运用渐进迭代方法和拉格朗日乘子法,使得极限曲面插值于初始控制顶点和法向量.实验结果证明了该方法可同时实现插值初始控制顶点和法向量,极限曲面具有较好的造型效果.     

基于蝶形细分自适应算法的三维地形仿真

基于格网法提出了蝶形细分自适应算法进行三维地形模拟,以原网格顶点的法向量为约束条件,通过对初始三角形控制网格进行多阶曲线迭代插值的非静态细分,实现几何造型.插值点的计算依据网格的局部几何特征,根据三角形网格上顶点的平坦度进行有选择性的自适应细分,同时对细分过程中产生的曲面裂缝加以弥补.地形仿真实例显示新的自适应细分方法可以很好地继承原始网格的形状特征,在曲面的光滑度和真实性上更加完善,加快了图形处理的速度.     

用逼近型√3细分方法构造闭三角网格的插值曲面

为了避免用逼近型3~(1/2)细分方法构造插值曲面过程中出现的烦琐运算,利用3细分方法极限点计算公式,提出一种用逼近型3~(1/2)细分方法构造闭三角网格插值曲面的方法.给定待插值的闭三角网格,先用一个新的几何规则与原3~(1/2)细分方法的拓扑规则细分一次得到一个初始网格,用3~(1/2)细分方法细分该初始网格得到插值曲面;新几何规则根据极限点公式确定,保证了初始网格的极限曲面插值待插值的三角网格.由于初始网格的顶点仅与待插值顶点2邻域内的点相关,所以插值曲面具有良好的局部性,即改变一个待插值点的位置时,只影响插值曲面在其附近的形状.该方法中只有确定初始网格顶点的几何规则与原3细分方法不同,故易于整合到原有的细分系统中.实验结果表明,该方法具有计算简单、有充分的自由度调整插值曲面的形状等特点,使得利用3~(1/2)细分方法构造三角网格的插值曲面变得极其简单.     

用逼近型3~(1/2)细分方法构造闭三角网格的插值曲面

为了避免用逼近型3~(1/2)细分方法构造插值曲面过程中出现的烦琐运算,利用3细分方法极限点计算公式,提出一种用逼近型3~(1/2)细分方法构造闭三角网格插值曲面的方法.给定待插值的闭三角网格,先用一个新的几何规则与原3~(1/2)细分方法的拓扑规则细分一次得到一个初始网格,用3~(1/2)细分方法细分该初始网格得到插值曲面;新几何规则根据极限点公式确定,保证了初始网格的极限曲面插值待插值的三角网格.由于初始网格的顶点仅与待插值顶点2邻域内的点相关,所以插值曲面具有良好的局部性,即改变一个待插值点的位置时,只影响插值曲面在其附近的形状.该方法中只有确定初始网格顶点的几何规则与原3细分方法不同,故易于整合到原有的细分系统中.实验结果表明,该方法具有计算简单、有充分的自由度调整插值曲面的形状等特点,使得利用3~(1/2)细分方法构造三角网格的插值曲面变得极其简单.     

几何迭代法及其应用综述

几何迭代法,又称渐进迭代逼近(progressive-iterative approximation,PIA),是一种具有明显几何意义的迭代方法.它通过不断调整曲线曲面的控制顶点,生成的极限曲线曲面插值(逼近)给定的数据点集.文中从理论和应用2个方面对几何迭代法进行了综述.在理论方面,介绍了插值型几何迭代法的迭代格式、收敛性证明、局部性质、加速方法,以及逼近型几何迭代法的迭代格式和收敛性证明等.进而,展示了几何迭代法在几个方面的成功应用,包括自适应数据拟合、大规模数据拟合、对称曲面拟合,以及插值给定位置、切矢量和曲率矢量的曲线迭代生成,有质量保证的四边网格和六面体网格生成,三变量B-spline体的生成等.     

基于C-C细分的四边形网格上插值光滑Bézier曲面的生成

在任意拓扑的四边形网格上构造光滑的曲面是计算机辅助几何设计中的一个重要问题.基于C-C细分,提出一种从四边形网格上生成插值网格顶点的光滑Bézier曲面片的算法.将输入四边形网格作为C-C细分的初始控制网格,在四边形网格的每张面上对应得到一张Bézier曲面,使Bézier曲面片逼近C-C细分极限曲面.曲面片在与奇异顶点相连的边界上G1连续,其他地方C2连续.为解决C-C细分的收缩问题,给出了基于误差控制的迭代扩张初始控制网格的方法,使从扩张后网格上生成的曲面插值于初始控制网格的顶点.实验结果表明,该算法效率高,生成的曲面具有较好的连续性,适用于对四边化后的网格模型上重建光滑的曲面.     

基于C—C细分的四边形网格上插值光滑Bezier曲面的生成

在任意拓扑的四边形网格上构造光滑的曲面是计算机辅助几何设计中的一个重要问题．基于C—C细分,提出一种从四边形网格上生成插值网格顶点的光滑Bezier曲面片的算法．将输入四边形网格作为C—C细分的初始控制网格,在四边形网格的每张面上对应得到一张Bezier曲面,使Bezier曲面片逼近C—C细分极限曲面．曲面片在与奇异顶点相连的边界上G^1连续,其他地方C^2连续．为解决C—C细分的收缩问题,给出了基于误差控制的迭代扩张初始控制网格的方法,使从扩张后网格上生成的曲面插值于初始控制网格的顶点．实验结果表明,该算法效率高,生成的曲面具有较好的连续性,适用于对四边化后的网格模型上重建光滑的曲面．     

渐进插值的LOOP曲面细分*

目前很多细分方法都存在不能用同一种方法处理封闭网格和开放网格的问题。对此,一种新的基于插值技术的LOOP曲面细分方法,其主要思想就是给定一个初始三角网格M,反复生成新的顶点,新顶点是通过其相邻顶点的约束求解得到的,从而构造一个新的控制网格M,在取极限的情况下,可以证明插值过程是收敛的;因为生成新顶点使用的是与其相连顶点的约束求解得到的,本质上是一种局部方法,所以,该方法很容易定义。它在本地方法和全局方法中都有优势,能处理任意顶点数量和任意拓扑结构的网格,从而产生一个光滑的曲面并忠实于给定曲面的形状,其控制     

Surface interpolation of meshes by geometric subdivision

Subdivision surfaces are generated by repeated approximation or interpolation from initial control meshes. In this paper, two new non-linear subdivision schemes, face based subdivision scheme and normal based subdivision scheme, are introduced for surface interpolation of triangular meshes. With a given coarse mesh more and more details will be added to the surface when the triangles have been split and refined. Because every intermediate mesh is a piecewise linear approximation to the final surface, the first type of subdivision scheme computes each new vertex as the solution to a least square fitting problem of selected old vertices and their neighboring triangles. Consequently, sharp features as well as smooth regions are generated automatically. For the second type of subdivision, the displacement for every new vertex is computed as a combination of normals at old vertices. By computing the vertex normals adaptively, the limit surface is G¹ smooth. The fairness of the interpolating surface can be improved further by using the neighboring faces. Because the new vertices by either of these two schemes depend on the local geometry, but not the vertex valences, the interpolating surface inherits the shape of the initial control mesh more fairly and naturally. Several examples are also presented to show the efficiency of the new algorithms.     

Progressive Interpolation based on Catmull‐Clark Subdivision Surfaces

We introduce a scheme for constructing a Catmull‐Clark subdivision surface that interpolates the vertices of a quadrilateral mesh with arbitrary topology. The basic idea here is to progressively modify the vertices of an original mesh to generate a new control mesh whose limit surface interpolates all vertices in the original mesh. The scheme is applicable to meshes with any size and any topology, and it has the advantages of both a local scheme and a global scheme.     

Conjugate-Gradient Progressive-Iterative Approximation for Loop and Catmull-Clark Subdivision Surface Interpolation

Loop and Catmull-Clark are the most famous approximation subdivision schemes, but their limit surfaces do not interpolate the vertices of the given mesh. Progressive-iterative approximation (PIA) is an efficient method for data interpolation and has a wide range of applications in many fields such as subdivision surface fitting, parametric curve and surface fitting among others. However, the convergence rate of classical PIA is slow. In this paper, we present a new and fast PIA format for constructing interpolation subdivision surface that interpolates the vertices of a mesh with arbitrary topology. The proposed method, named Conjugate-Gradient Progressive-Iterative Approximation (CG-PIA), is based on the Conjugate-Gradient Iterative algorithm and the Progressive Iterative Approximation (PIA) algorithm. The method is presented using Loop and Catmull-Clark subdivision surfaces. CG-PIA preserves the features of the classical PIA method, such as the advantages of both the local and global scheme and resemblance with the given mesh. Moreover, CG-PIA has the following features. 1) It has a faster convergence rate compared with the classical PIA and W-PIA. 2) CG-PIA avoids the selection of weights compared with W-PIA. 3) CG-PIA does not need to modify the subdivision schemes compared with other methods with fairness measure. Numerous examples for Loop and Catmull-Clark subdivision surfaces are provided in this paper to demonstrate the efficiency and effectiveness of CG-PIA.     

Making Doo-Sabin surface interpolation always work over irregular meshes

This paper presents a reliable method for constructing a control mesh whose Doo-Sabin subdivision surface interpolates the vertices of a given mesh with arbitrary topology. The method improves on existing techniques in two respects: (1) it is guaranteed to always work for meshes of arbitrary topological type; (2) there is no need to solve a system of linear equations to obtain the control points. Extensions to include normal vector interpolation and/or shape adjustment are also discussed.     

Fitting Sharp Features with Loop Subdivision Surfaces

Various methods have been proposed for fitting subdivision surfaces to different forms of shape data (e.g., dense meshes or point clouds), but none of these methods effectively deals with shapes with sharp features, that is, creases, darts and corners. We present an effective method for fitting a Loop subdivision surface to a dense triangle mesh with sharp features. Our contribution is a new exact evaluation scheme for the Loop subdivision with all types of sharp features, which enables us to compute a fitting Loop subdivision surface for shapes with sharp features in an optimization framework. With an initial control mesh obtained from simplifying the input dense mesh using QEM, our fitting algorithm employs an iterative method to solve a nonlinear least squares problem based on the squared distances from the input mesh vertices to the fitting subdivision surface. This optimization framework depends critically on the ability to express these distances as quadratic functions of control mesh vertices using our exact evaluation scheme near sharp features. Experimental results are presented to demonstrate the effectiveness of the method.     

Similarity based interpolation using Catmull–Clark subdivision surfaces

A new method for constructing a Catmull–Clark subdivision surface (CCSS) that interpolates the vertices of a given mesh with arbitrary topology is presented. The new method handles both open and closed meshes. Normals or derivatives specified at any vertices of the mesh (which can actually be anywhere) can also be interpolated. The construction process is based on the assumption that, in addition to interpolating the vertices of the given mesh, the interpolating surface is also similar to the limit surface of the given mesh. Therefore, construction of the interpolating surface can use information from the given mesh as well as its limit surface. This approach, called similarity based interpolation, gives us more control on the smoothness of the interpolating surface and, consequently, avoids the need of shape fairing in the construction of the interpolating surface. The computation of the interpolating surface’s control mesh follows a new approach, which does not require the resulting global linear system to be solvable. An approximate solution provided by any fast iterative linear system solver is sufficient. Nevertheless, interpolation of the given mesh is guaranteed. This is an important improvement over previous methods because with these features, the new method can handle meshes with large number of vertices efficiently. Although the new method is presented for CCSSs, the concept of similarity based interpolation can be used for other subdivision surfaces as well.