优化变形能的平面多边形同构剖分

平面多边形间的同构三角剖分是平面形状渐进过渡与插值的基础,降低对应三角形的变形程度是获得高质量应用的关键.文中提出一种基于变形能优化的2个平面多边形的同构剖分算法,其中包含同构剖分生成和变形能最小化2个模块.首先根据用户指定的对应特征点对多边形进行顶点重采样,得到顶点一一对应的2个多边形;然后利用带约束的Delaunay剖分对其中的一个多边形进行三角化,得到源网格;再用重心坐标将源网格的内部顶点嵌入到另一个多边形得到同构剖分(目标网格);最后逐一检查三角形的变形能,对源网格中变形能超过阈值的三角形进行细分,用同构剖分模块生成新的目标网格.实验及数据统计分析表明,该算法可以得到较好的同构三角剖分,提升网格质量,并能很好地避免纹理细节失真.     

迭代逼近坐标

广义重心坐标能把多边形内任意一点表示为其顶点的线性组合,因此广泛应用于计算机图形学等领域.本文用渐进逼近的思想计算广义重心坐标.给定多边形及其内一点,首先将多边形映射到以该点为圆心的单位圆上,依次连接映射到同一圆上的各边中点,形成新的圆内接多边形.然后构造以多边形相邻两个点为顶点,其余点的加权和为另一顶点的三角形,并在...     

智能配镜三维特征参数提取方法研究

摘 要：针对智能配镜中三维面部特征点提取算法复杂度较高的问题,提出一种将三维点 云转换为映射图像定位特征点的方法。采用 Voronoi 方法计算面部三角网格各顶点处的高斯曲 率、平均曲率。选取鼻尖、眼角等曲率特征明显的区域估计面部点云姿态。根据曲率旋转不变 性,使用初选的点云方向向量简化旋转矩阵的计算,使面部点云正面朝向视点。将点云映射转 换为图像,三维网格模型中三角面片一对一映射到图像中的三角形。搭建卷积神经网络,使用 Texas 3DFRD 数据集进行模型训练。进行人脸对齐,预测所得各面部特征点分别限制在图像某 三角形中。根据图像中三角形映射查找三维网格模型中对应三角面片,通过三角面片顶点坐标 计算配镜所需的面部特征点位置坐标,实现配镜特征参数的提取。     

各向异性广义重心坐标及其应用EI北大核心CSCD

可在任意多边形上定义的且具有解析表达式的广义重心坐标通常不具有非负性,目前对广义重心坐标各向异性的工作相对较少.针对上述问题,提出了一种可在任意多边形上定义的,且具有非负性和各向异性的广义重心坐标——各向异性坐标.首先,对原始多边形内任意一点,生成该点的可见多边形;其次,基于Power图的相关性质,计算该点关于可见多边形的各向异性坐标;最后,将可见多边形上的各向异性坐标分解到原始多边形上.在图像变形的应用中,各向异性坐标提供了3个几何意义清晰的参数,以供用户直观地调整不同的变形效果;在函数插值的实验中,采用各向异性坐标得到的均方根误差比采用均值坐标时平均降低了44%;在图像逼近的实验中,采用各向异性坐标可有效减少在图像变化剧烈的区域处产生的伪影.     

基于四边形网格均值坐标的K-2环网格曲面构造

为在曲面造型中避免产生扭曲、褶皱等现象,将四边形网格中内点的 K-2 环网格作为控制网格, 提出一种简单、灵活的曲面构造方法。给定一个 K-2 环控制网格,构造一个与其具有同样拓扑结构的平面网格。 再将平面网格拓展成空间四边形网格,同时在平面网格内进行采样。然后计算采样点关于空间四边形网格顶点 的四边形网格均值坐标,最后利用四边形网格均值坐标生成曲面,保证曲面上的每一点都满足 C∞ 。在这个过 程中设置了一个全局形状因子 h,用于控制曲面与初始控制网格的逼近程度,通过实例证明,h 越小,曲面越 逼近初始控制网格。     

基于三角形骨架坐标的图象渐变算法

为快速进行不规则多边形区域内的数字图象渐变处理,提出了一种基于三角形骨架坐标的图象渐变算法,即先将图象区域分割为若干个三角形区域,再逐个对这些三角形区域建立象素点的骨架坐标,这样三角形骨架外壳的改变就会带动其内部图象的渐变,并根据骨架坐标变换,推导三角形区域内象素点坐标随外壳三角形顶点改变的计算公式,进而建立了骨架外壳改变后的新象素点与原始象素点间的颜色对应关系。利用该不规则多边形区域内的图象渐变算法,可解决运动模拟等常见图象的变形问题。     

基于粒子群优化算法的三角网格孔洞修补

为了对三角网格模型中的复杂孔洞和曲率变化较剧烈部位处的孔洞进行修补,提出了一种基于粒子群优化算法（PSO）的三角网格孔洞修补算法。首先对孔洞多边形进行初始网格化,并计算所有网格顶点的梯度值,然后采用PSO搜索与孔洞边缘顶点梯度匹配的点集,最后根据孔洞匹配点集中顶点的梯度对孔洞中的初始网格进行修正,实现三角网格孔洞的修补。实验表明,该算法对各种复杂或曲率变化较大的孔洞,都有很好的修补效果。     

基于重新划分的三角形网格简化的一种改进算法

基于重新划分的三角形网格简化方法能自动生成多细节层次模型，它的基本思想是:根据三角形网格的局部几何和拓扑特征将一定数量的点分布到原网格上,生成一个中间网格,移去中间网格中的老顶点,并对产生的多边形区域进行局部三角化,最后形成以新点为顶点的三角形网格.本文在已有算法的基础上,提出了一种分布新点的算法,从而克服了原有方法的局限性.它利用三角形顶点的曲率和三角形的面积两个因素来反映网格在每个三角形处的特征.文中给出的一组实例说明了算法的有效性.     

基于三角基的平面多边形变形

本文讲解在VC 6.0环境下解通过对初始多边形和目标多边形进行Delaunay三角剖分,给出描述三角形网格各顶点空间位置的内在结构矩阵,然后插值相应的三角网格结构矩阵,实现多边形之间的形状变化。     

隐式曲面重新多边形化

首先用Bloomenthal的多边形化算法生成一个粗糙的初始网格;然后在初始网格上分布若干个新顶点,新顶点可以均匀分布,也可以按曲率分布;再把初始网格上的老顶点和新顶点连接起来,生成一个中间网格,从中间网格上删除初始网格上的老顶点,得到重新多边形化的网格;最后细分这个网格．实验结果表明：该算法可以生成近似等边的、大小由曲率指导的三角网格．     

Maximum Likelihood Coordinates

Any point inside a d-dimensional simplex can be expressed in a unique way as a convex combination of the simplex's vertices, and the coefficients of this combination are called the barycentric coordinates of the point. The idea of barycentric coordinates extends to general polytopes with n vertices, but they are no longer unique if n > d+1. Several constructions of such generalized barycentric coordinates have been proposed, in particular for polygons and polyhedra, but most approaches cannot guarantee the non-negativity of the coordinates, which is important for applications like image warping and mesh deformation. We present a novel construction of non-negative and smooth generalized barycentric coordinates for arbitrary simple polygons, which extends to higher dimensions and can include isolated interior points. Our approach is inspired by maximum entropy coordinates, as it also uses a statistical model to define coordinates for convex polygons, but our generalization to non-convex shapes is different and based instead on the project-and-smooth idea of iterative coordinates. We show that our coordinates and their gradients can be evaluated efficiently and provide several examples that illustrate their advantages over previous constructions.     

Approximating Planar Conformal Maps Using Regular Polygonal Meshes

Continuous conformal maps are typically approximated numerically using a triangle mesh which discretizes the plane. Computing a conformal map subject to user‐provided constraints then reduces to a sparse linear system, minimizing a quadratic ‘conformal energy’. We address the more general case of non‐triangular elements, and provide a complete analysis of the case where the plane is discretized using a mesh of regular polygons, e.g. equilateral triangles, squares and hexagons, whose interiors are mapped using barycentric coordinate functions. We demonstrate experimentally that faster convergence to continuous conformal maps may be obtained this way. We provide a formulation of the problem and its solution using complex number algebra, significantly simplifying the notation. We examine a number of common barycentric coordinate functions and demonstrate that superior approximation to harmonic coordinates of a polygon are achieved by the Moving Least Squares coordinates. We also provide a simple iterative algorithm to invert barycentric maps of regular polygon meshes, allowing to apply them in practical applications, e.g. for texture mapping.     

Maximum Entropy Coordinates for Arbitrary Polytopes

Barycentric coordinates can be used to express any point inside a triangle as a unique convex combination of the triangle's vertices, and they provide a convenient way to linearly interpolate data that is given at the vertices of a triangle. In recent years, the ideas of barycentric coordinates and barycentric interpolation have been extended to arbitrary polygons in the plane and general polytopes in higher dimensions, which in turn has led to novel solutions in applications like mesh parameterization, image warping, and mesh deformation. In this paper we introduce a new generalization of barycentric coordinates that stems from the maximum entropy principle. The coordinates are guaranteed to be positive inside any planar polygon, can be evaluated efficiently by solving a convex optimization problem with Newton's method, and experimental evidence indicates that they are smooth inside the domain. Moreover, the construction of these coordinates can be extended to arbitrary polyhedra and higher‐dimensional polytopes.     

均值重心坐标的鲁棒算法及其几何性质

均值重心坐标不仅适用于凸多边形，而且适用于星形多边形．已有定义方法在多边形边界处具有奇异性，计算时容易产生数值不稳定问题，因而不适用于几何计算．首先分析和比较了已有的各种重心坐标的定义方法，提出了一种鲁棒的均值重心坐标计算方法，并且从理论和实验两方面证明了均值重心坐标在多边形边界上的Lagrange性质和线性性质．     

基于Delaunay三角网的任意多边形三角剖分算法研究

文章通过分析现有多边形三角剖分算法,给出一种基于Delaunay三角网的任意复杂多边形三角剖分的改进算法。算法首先忽略多边形顶点与边线间的逻辑关系,将其看做散乱顶点的集合,然后采用Delaunay三角化方法对点集进行合理剖分,再依据多边形顶点及边线间的逻辑关系,逐一将那些不合理的三角网剔除,最终重新组合出符合要求的三角网格。     

Barycentric Coordinates on Surfaces

This paper introduces a method for defining and efficiently computing barycentric coordinates with respect to polygons on general surfaces. Our construction is geared towards injective polygons (polygons that can be enclosed in a metric ball of an appropriate size) and is based on replacing the linear precision property of planar coordinates by a requirement in terms of center of mass, and generalizing this requirement to the surface setting. We show that the resulting surface barycentric coordinates can be computed using planar barycentric coordinates with respect to a polygon in the tangent plane. We prove theoretically that the surface coordinates properly generalize the planar coordinates and carry some of their useful properties such as unique reconstruction of a point given its coordinates, uniqueness for triangles, edge linearity, similarity invariance, and smoothness; in addition, these coordinates are insensitive to isometric deformations and can be used to reconstruct isometries. We show empirically that surface coordinates are shape‐aware with consistent gross behavior across different surfaces, are well‐behaved for different polygon types/locations on variety of surface forms, and that they are fast to compute. Finally, we demonstrate effectiveness of surface coordinates for interpolation, decal mapping, and correspondence refinement.     

Robust and Optimized Algorithms for the Point‐in‐Polygon Inclusion Test without Pre‐processing

In this work we present new point inclusion algorithms for non‐convex polygons. These algorithms do not perform any pre‐processing or any type of decomposition nor features classification, which makes them especially suitable for deformable or moving polygons. The algorithms are more accurate and robust than others in the sense that they consider the inclusion of the point in the vertices and edges of the polygon, and deal with the special cases correctly. In order to perform this inclusion test efficiently, they use the sign of the barycentric coordinates of the test point with regard to the triangles formed by the edges and an origin that depends on the test point. This set of triangles, which is a special simplicial covering of the polygon, is constructed after a transformation of the polygon that simplifies the calculations involved in the inclusion test. Then, an appropriate ordering of the rejection tests allows us to optimize this method. Our algorithms have been tested for robustness and compared with ray‐crossing methods, showing a significant improvement.     

基于特定边界的组合保角球面参数化

针对亏格为零的流形三角网格模型,提出一种基于特定边界的组合保角球面参数化方法。该方法采用平均值坐标计算出原始三角网格模型各顶点间相关的权数,然后用这个权数去修正球面域上的顶点坐标得到新的具有保角性质的顶点坐标,再利用Möbius变换把新生成的球面域质心转化为球心,使其面积的变形程度降低,最后得到一个精度更高的初始球面域。实验结果表明该方法是有效的,且具有变形小、效率高的特点。     

广义重心坐标的递推关系

从线性方程组解空间的角度理解广义重心坐标(GBCs),给出平面重心坐标从n 边形 到n 1边形的递推关系式。将构造重心坐标的问题转化为构造函数的问题,不需考虑坐标函数的 几何意义,选取满足约束条件的函数即可构造重心坐标。在推导过程中,n 1边形(n≥3)可看 作n边形与一顶点的组合,将该顶点用n边形的顶点线性表出,可将n 1边形上的重心坐标化为 n边形上的齐次坐标(homogeneous coordinates)。为第n 1个坐标函数施加一定限制条件,即得到 n 边形上一组重心坐标。     

Scale-aware shape manipulation

A novel representation of a triangular mesh surface using a set of scale-inva~iant measures is proposed. The measures consist of angles of the triangles （triangle angles） and dihedral angles along the edges （edge angles） which are scale and rigidity independent. The vertex coordinates for a mesh give its scale-invariant measures, unique up to scale, rotation, and translation. Based on the representation of mesh using scale-invariant measures, a two-step iterative deformation algorithm is proposed, which can arbitrarily edit the mesh through simple handles interaction. The algorithm can explicitly preserve the local geometric details as much as possible in different scales even under severe editing operations including rotation, scaling, and shearing. The efficiency and robustness of the proposed algorithm are demonstrated by examples.