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.     

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.     

Moving Least Squares Coordinates

We propose a new family of barycentric coordinates that have closed‐forms for arbitrary 2D polygons. These coordinates are easy to compute and have linear precision even for open polygons. Not only do these coordinates have linear precision, but we can create coordinates that reproduce polynomials of a set degree m as long as degree m polynomials are specified along the boundary of the polygon. We also show how to extend these coordinates to interpolate derivatives specified on the boundary.     

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.     

矩阵重心坐标

在二维重心坐标——复数重心坐标的基础上引入二维矩阵重心坐标的概念,并利用球面坐标将二维矩阵重心坐标推广到三维.三维矩阵重心坐标适用于三角控制网格、四边形控制网格甚至一般的混合控制网格.对所提出的重心坐标性质进行了研究,发现其满足大部分好的重心坐标所应具有的性质.最后对矩阵重心坐标在三维网格模型中的应用进行了细致的实验,分析了它的优缺点.     

A Complex View of Barycentric Mappings

Barycentric coordinates are very popular for interpolating data values on polyhedral domains. It has been recently shown that expressing them as complex functions has various advantages when interpolating two‐dimensional data in the plane, and in particular for holomorphic maps. We extend and generalize these results by investigating the complex representation of real‐valued barycentric coordinates, when applied to planar domains. We show how the construction for generating real‐valued barycentric coordinates from a given weight function can be applied to generating complex‐valued coordinates, thus deriving complex expressions for the classical barycentric coordinates: Wachspress, mean value, and discrete harmonic. Furthermore, we show that a complex barycentric map admits the intuitive interpretation as a complex‐weighted combination of edge‐to‐edge similarity transformations, allowing the design of “home‐made” barycentric maps with desirable properties. Thus, using the tools of complex analysis, we provide a methodology for analyzing existing barycentric mappings, as well as designing new ones.     

Biharmonic Coordinates

Barycentric coordinates are an established mathematical tool in computer graphics and geometry processing, providing a convenient way of interpolating scalar or vector data from the boundary of a planar domain to its interior. Many different recipes for barycentric coordinates exist, some offering the convenience of a closed‐form expression, some providing other desirable properties at the expense of longer computation times. For example, harmonic coordinates, which are solutions to the Laplace equation, provide a long list of desirable properties (making them suitable for a wide range of applications), but lack a closed‐form expression. We derive a new type of barycentric coordinates based on solutions to the biharmonic equation. These coordinates can be considered a natural generalization of harmonic coordinates, with the additional ability to interpolate boundary derivative data. We provide an efficient and accurate way to numerically compute the biharmonic coordinates and demonstrate their advantages over existing schemes. We show that biharmonic coordinates are especially appealing for (but not limited to) 2D shape and image deformation and have clear advantages over existing deformation methods.     

结合广义重心坐标与Voronoi 剖分的函数分片逼近

结合广义重心坐标理论,提出了一个新方法,以解决在平面区域上的函数逼近问题。 该方法通过构建基于广义重心坐标的最优分片函数来逼近目标函数。采用Voronoi 图来划分区域, 并提出一个度量逼近误差的能量函数。推导出该函数的导数后,采用一种高效的Voronoi 节点更 新方法来获得区域的最优剖分,并通过最优剖分构建最优分片函数。由于该方法对不连续函数具 有良好地逼近能力,因此将其应用在图像逼近问题中。分别在解析函数和彩色图像上对该方法进 行实验,均获得了很好的逼近效果。     

基于衍生多边形的混合坐标

将多边形三角化,利用三角网格将三角形衍生为点多边形、边多边形和面多边形,再根据已有的重心坐标提出基于衍生多边形的混合坐标.首先在三角网格内根据初始多边形内部一点所在的三角形得到衍生多边形,然后使用调和坐标、局部重心坐标、迭代坐标中任意一种计算衍生多边形的顶点关于初始多边形顶点的重心坐标,再使用迭代坐标计算初始多边形内部...     

A new non-negative matrix factorization method based on barycentric coordinates for endmember extraction in hyperspectral remote sensing

In this study, we present a new non-negative matrix factorization (NMF) method using the pixel's barycentric coordinates for endmember extraction, named BC-NMF. Our method applies the geometrical property of simplex in the calculation of abundance fraction. That is, for any pixel in an image, its abundance fractions are its barycentric coordinates within the endmember coordinate system. Experiments using both simulated and real hyperspectral images show that BC-NMF can generate endmembers with higher accuracy and lower computational complexity than NMF.     

Positive Gordon–Wixom coordinates

We introduce a new construction of transfinite barycentric coordinates for arbitrary closed sets in two dimensions. Our method extends weighted Gordon–Wixom interpolation to non-convex shapes and produces coordinates that are positive everywhere in the interior of the domain and that are smooth for shapes with smooth boundaries. We achieve these properties by using the distance to lines tangent to the boundary curve to define a weight function that is positive and smooth. We derive closed-form expressions for arbitrary polygons in two dimensions and compare the basis functions of our coordinates with several other types of barycentric coordinates.     

A Multi‐sided Bézier Patch with a Simple Control Structure

A new n‐sided surface scheme is presented, that generalizes tensor product Bézier patches. Boundaries and corresponding cross‐derivatives are specified as conventional Bézier surfaces of arbitrary degrees. The surface is defined over a convex polygonal domain; local coordinates are computed from generalized barycentric coordinates; control points are multiplied by weighted, biparametric Bernstein functions. A method for interpolating a middle point is also presented. This Generalized Bézier (GB) patch is based on a new displacement scheme that builds up multi‐sided patches as a combination of a base patch, n displacement patches and an interior patch; this is considered to be an alternative to the Boolean sum concept. The input ribbons may have different degrees, but the final patch representation has a uniform degree. Interior control points—other than those specified by the user—are placed automatically by a special degree elevation algorithm. GB patches connect to adjacent Bézier surfaces with G¹continuity. The control structure is simple and intuitive; the number of control points is proportional to those of quadrilateral control grids. The scheme is introduced through simple examples; suggestions for future work are also discussed.     

Complex Transfinite Barycentric Mappings with Similarity Kernels

Transfinite barycentric kernels are the continuous version of traditional barycentric coordinates and are used to define interpolants of values given on a smooth planar contour. When the data is two‐dimensional, i.e. the boundary of a planar map, these kernels may be conveniently expressed using complex number algebra, simplifying much of the notation and results. In this paper we develop some of the basic complex‐valued algebra needed to describe these planar maps, and use it to define similarity kernels, a natural alternative to the usual barycentric kernels. We develop the theory behind similarity kernels, explore their properties, and show that the transfinite versions of the popular three‐point barycentric coordinates (Laplace, mean value and Wachspress) have surprisingly simple similarity kernels. We furthermore show how similarity kernels may be used to invert injective transfinite barycentric mappings using an iterative algorithm which converges quite rapidly. This is useful for rendering images deformed by planar barycentric mappings.     

基于矩特性的变形图像矫正

通过求出车辆牌照二值图像中每个字符区域的范围,运用图像的矩特性计算每个字符区域的面积和重心坐标,由重心坐标拟合直线,得到牌照的水平倾斜角度对有倾斜的牌照图片进行矫正。     

Spherical Triangular B-splines with Application to Data Fitting

Triangular B-splines surfaces are a tool for representing arbitrary piecewise polynomial surfaces over planar triangulations, while automatically maintaining continuity properties across patch boundaries. Recently, Alfeld et al. [1] introduced the concept of spherical barycentric coordinates which allowed them to formulate Bernstein-Bézier polynomials over the sphere. In this paper we use the concept of spherical barycentric coordinates to develop a similar formulation for triangular B-splines, which we call spherical triangular B-splines. These splines defined over spherical triangulations share the same continuity properties and similar evaluation algorithms with their planar counterparts, but possess none of the annoying degeneracies found when trying to represent closed surfaces using planar parametric surfaces. We also present an example showing the use of these splines for approximating spherical scattered data.     

基于稀疏解组合优化的广义重心坐标

根据广义重心坐标线性运算的性质与特点,运用广义重心坐标的稀疏解权函数的 调和平均组合方法,对空间凸多面体顶点设计了一种求解广义重心坐标的算法,且权函数是带 有保形参数的一元函数,因而具有保形优化的特点。构造了 2 种不同类型的带形参权函数,运 用不同权函数及其参数的广义重心坐标将平面图形映射到空间曲面的实例进行了分析,并应用 重心坐标常用的等值线工具对保形性进行了比较。     

质心坐标变换及其在纹理映射均匀化中的应用

在现有质心坐标变换方法基础上,提出一种改进方法——均匀面积质心变换方法：在某一顶点邻域中,采用相应点所对应的边高比之和作为质心坐标进行分析推导,并将其应用到复杂三维形体的纹理映射均匀化中．首先通过面积权重质心坐标变换将复杂三维网格映射到平面上;在此基础上进行均匀面积质心坐标变换,就可使平面网格较均匀地分布．求解其纹理坐标可实现采用单幅图像的纹理映射均匀化．通过典型三维模型的实验和比较可以看到：采用文中方法所获得的纹理映射均匀化效果较现有的保角变换、保面积变换方法有显著改善,而且算法简单、稳定、快速．     

Poisson‐Based Weight Reduction of Animated Meshes

While animation using barycentric coordinates or other automatic weight assignment methods has become a popular method for shape deformation, the global nature of the weights limits their use for real‐time applications. We present a method that reduces the number of control points influencing a vertex to a user‐specified number such that the deformations created by the reduced weight set resemble that of the original deformation. To do so we show how to set up a Poisson minimization problem to solve for a reduced weight set and illustrate its advantages over other weight reduction methods. Not only does weight reduction lower the amount of storage space necessary to deform these models but also allows GPU acceleration of the resulting deformations. Our experiments show that we can achieve a factor of 100 increase in speed over CPU deformations using the full weight set, which makes real‐time deformations of large models possible.     

A Family of Barycentric Coordinates for Co‐Dimension 1 Manifolds with Simplicial Facets

We construct a family of barycentric coordinates for 2D shapes including non‐convex shapes, shapes with boundaries, and skeletons. Furthermore, we extend these coordinates to 3D and arbitrary dimension. Our approach modifies the construction of the Floater‐Hormann‐Kós family of barycentric coordinates for 2D convex shapes. We show why such coordinates are restricted to convex shapes and show how to modify these coordinates to extend to discrete manifolds of co‐dimension 1 whose boundaries are composed of simplicial facets. Our coordinates are well‐defined everywhere (no poles) and easy to evaluate. While our construction is widely applicable to many domains, we show several examples related to image and mesh deformation.