Rational bicubic simple quadrilateral mesh surfaces

In free-form modeling a closed smooth piecewise surface is highly desirable when the smoothness across the boundaries of patches can be represented within the formulation. Closed, smooth, piecewise bicubic surfaces, defined on simple quadrilateral mesh. (SQM), may be defined as SQM surfaces. We have extended previous work on SQM surfaces and described the surface representation in rational form. The global constraint of the control parameters associated with each control vertex is relaxed. The new local shape-control parameters with their larger range of usability further enhance the power of this free-form surface design scheme. We have also provided more B-spline functions. A complete set of B-spline functions for various topologies of the SQM is now available. Examples demonstrate that editing of shapes for reasonably complex objects can be carried out on an SGI Personal Iris machine at an interactive rate.     

4阶均匀代数三角样条空间的拟Legendre基

为解决代数三角样条空间上正交基的理论问题,提出了4阶均匀代数三角样条空间上构造正交基的方法.该方法利用6阶C-B样条基函数构造一组辅助函数,并以这组辅助函数的二阶导数形式定义样条空间上的一组正交基,称为拟Legendre基.实例结果表明,使用这组正交基可以简化内积计算,便于最佳平方逼近问题求解.     

Multiresolution for Closed Curves and Surfaces Using Wavelets

Multiresolution modeling is becoming a powerful tool for fast display, and geometric data compression and transmission of complex shapes. Most of the existing literatures investigating the multiresolution for B-spline curves and surfaces are concentrated on open ones. In this paper, we focus on the multiresolution representations and editing of closed B-spline curves and surfaces using wavelets. A repetition approach is adopted for the multiresolution analysis of closed B-spline curves and surfaces. Since the closed curve or surface itself is periodic, it can overcome the drawback brought by the repetition method, i.e. introducing the discontinuities at the boundaries. Based on the models at different multiresolution levels, the multiresolution editing methods of closed curves and surfaces are introduced. Users can edit the overall shape of a closed one while preserving its details, or change its details without affecting its overall shape.     

Parting line formation by slicing a 3D CAD model

An effective computer-aided parting line/surface formation algorithm can increase the overall efficiency in the mould design and manufacturing processes. The presence of free-form surfaces in a product model imposes a burden on mould makers to determine the parting line and parting surfaces. Previously proposed algorithms, although available, are few, and mainly deal with product with planar or simple curved surfaces. A new algorithm, which adopts an uneven slicing on the product model, is proposed. The algorithm provides a quick and effective way to locate the parting line and parting surface of a free-form product model.     

A theory for multiresolution signal decomposition: the waveletrepresentation

Multiresolution representations are effective for analyzing the information content of images. The properties of the operator which approximates a signal at a given resolution were studied. It is shown that the difference of information between the approximation of a signal at the resolutions 2^j+1 and 2^j (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L²(Rⁿ), the vector space of measurable, square-integrable n-dimensional functions. In L²(R), a wavelet orthonormal basis is a family of functions which is built by dilating and translating a unique function ψ(x). This decomposition defines an orthogonal multiresolution representation called a wavelet representation. It is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters. Wavelet representation lies between the spatial and Fourier domains. For images, the wavelet representation differentiates several spatial orientations. The application of this representation to data compression in image coding, texture discrimination and fractal analysis is discussed     

分形曲线生成的频域方法

目的 分形几何学的理论研究与应用实践方兴未艾,在分形的计算机生成领域,传统方法是在空间域中,通过对生成元的迭代操作而形成。为了扩展分形的生成方法,本文将频谱分析引入到分形几何中。方法 正交函数系是频谱分析的核心问题之一。考虑到分形曲线是一类连续而不光滑的折线型信号,通常的三角函数（Fourier变换）、连续小波变换仅适用于光滑的对象,否则会出现所谓“Gibbs现象”;另一方面,以V-系统为代表的正交分段多项式函数系适用于表达包含间断性的对象,否则会出现信息冗余。因此,通常的正交函数系均不适合分形的频谱表达与分析。针对分形曲线的特点,本文将其视为一次样条函数,通过引入一类正交样条函数系-Franklin函数系,实现了对分形曲线的有限项精确正交表达,得到Franklin频谱,从而完成分形的时频变换。然后,对Franklin频谱系数在不同尺度上进行修改。最后,通过正交重构得到新的分形。结果 对比实验验证了Franklin函数系在分形曲线频域表达方面的优越之处,它既能通过最小项数实现分形的正交表达,而且不会出现Gibbs现象。本文以von Koch曲线、Sierpinski square曲线和Hilbert曲线这3个经典分形为例,通过对Franklin谱在不同尺度上的自由调节,能够方便地生成大量形态各异的新的分形曲线。结论 Franklin谱不仅能够实现对分形曲线的有限精确重构,而且还能在不同尺度上刻画分形的形态特征。基于Franklin频谱调节实现的分形生成方法,只要修改频谱就可以得到大量的新型分形曲线,而且这些分形的样式千变万化,几乎不可预测,这种分形生成方式为分形设计带来了巨大的自由空间,为分形的生成提供了新的思路与方案。     

Bayesian smoothing spline analysis of variance

Smoothing spline ANOVA (SSANOVA) provides an approach to semiparametric function estimation based on an ANOVA type of decomposition. Wahba et al. (1995) decomposed the regression function based on a tensor sum decomposition of inner product spaces into orthogonal subspaces, so the effects of the estimated functions from each subspace can be viewed independently. Recent research related to smoothing spline ANOVA focuses on either frequentist approaches or a Bayesian framework for variable selection and prediction. In our approach, we seek “objective” priors especially suited to estimation. The prior for linear terms including level effects is a variant of the Zellner–Siow prior (Zellner and Siow, 1980), and the prior for a smooth effect is specified in terms of effective degrees of freedom. We study this fully Bayesian SSANOVA model for Gaussian response variables, and the method is illustrated with a real data set.     

Efficient Space-Time Spectral Methods for Second-Order Problems on Unbounded Domains

In this paper, we propose efficient space-time spectral methods for problems on unbounded domains. For this purpose, we first introduce two series of new basis functions on the half/whole line by matrix decomposition techniques. The new basis functions are mutually orthogonal in both \(L^2\) and \(H^1\) inner products, and lead to diagonal systems for second order problems with constant coefficients. Then we construct efficient space-time spectral methods based on Laguerre/Hermite-Galerkin methods in space and dual-Petrov-Galerkin formulations in time for problems defined on unbounded domains. Using these suggested methods, higher accuracy can be obtained. We also demonstrate that the use of simultaneously orthogonal basis functions in space may greatly simplify the implementation of the space-time spectral methods.     

Decompositions of finite games: From weighted inner product to standard inner product

To investigate the topological structure of finite games, various decomposions of finite games have been proposed. The inner product of vectors plays a key role in the decomposition of finite games. This paper considers the effect of different inner products on the orthogonal decomposition of finite games. We found that only when the compatible condition is satisfied, a common decomposition can be induced by the standard inner product and the weighted inner product simultaneously. To explain the result, we studied the existing decompositions, including potential based decomposition, zero‐sum based decomposition, and normalization based decomposition. For zero‐sum based decomposition and normalization based decomposition, we redefine their subspaces in a linear algebraic framework, which shows their physical meanings clearly. Bases of subspaces in these two decompositions are constructed.     

基于两变量Krawtchouk矩的图像重建

传统的离散正交Krawtchouk矩的基函数由两个单变量的Krawtchouk多项式乘积构成,它割裂平面两个方向之间的联系。提出了一种新的、以两变量Krawtchouk正交多项式为基函数的图像矩,并推导了正则化后两变量多项式的简单的计算方法。重建实验结果表明,相对于同系数的单变量的离散正交矩,两变量离散正交矩的重建误差更小。     

Variational Modeling of Free-form Curve and Surface Using Wavelet Basis Functions

Variational modeling approach is often used to interactively design free-form curves and surfaces. Traditionally, a variational problem can be transformed to the optimization of control points. Unfortunately, as the number of basis functions grows, the local support property of B-spline often makes the computation of an optimization system time-consuming. To solve this problem, wavelet basis instead of B-spline basis is used to represent the curves or surfaces. Because the wavelet basis is a hierarchical basis with multiresolution property, the coarse wavelet basis can be used to describe the overall shape of the curves/surfaces, while the finer wavelet basis used to describe the details of the curves/surfaces. Thus, the computing speed of the optimization system can be raised greatly.     

基于小波的B样条曲线多分辨表示及编辑

多分辨表示方法为曲线提供了更为灵活的表达方式,使得我们可以在不同分辨率下对曲线进行编辑,小波技术是实现曲线多分辨表示的一种新颖方法,已有许多论文从理论上论述了这项技术,文中从几何概念出发,由浅入深地论述了基于小波的准均匀三次B样条曲线多分辨表示的原理及其实现,并通过实例描述了B样条曲线的多分辨编辑。     

Some applications of Loop-subdivision wavelet tight frames to?the?processing of 3D graphics

Multiresolution analysis based on subdivision wavelets is an important method of 3D graphics processing. Many applications of this method have been studied and developed, including denoising, compression, progressive transmission, multiresolution editing and so on. Recently Charina and St?ckler firstly gave the explicit construction of wavelet tight frame transform for subdivision surfaces with irregular vertices, which made its practical applications to 3D graphics became a subject worthy of investigation. Based on the works of Charina and St?ckler, we present in detail the wavelet tight frame decomposition and reconstruction formulas for Loop-subdivision scheme. We further implement the algorithm and apply it to the denoising, compression and progressive transmission of 3D graphics. By comparing it with the biorthogonal Loop-subdivision wavelets of Bertram, the numerical results illustrate the good performance of the algorithm. Since multiresolution analysis based on subdivision wavelets or subdivision wavelet tight frames requires the input mesh to be semi-regular, we also propose a simple remeshing algorithm for constructing meshes which not only have subdivision connectivity but also approximate the input mesh.     

Normal Computation for Discrete Surfaces in 3D Space

Associating normal vectors to surfaces is essential for many rendering algorithms. We introduce a new method to compute normals on discrete surfaces in object space. Assuming that the surface separates space locally into two disjoint subsets, each of these subsets contains implicitly information about the surface inclination. Considering one of these subsets in a small neighbourhood of a surface point enables us to derive the surface normal from this set. We show that this leads to exact results for C¹ continuous surfaces in R³. Furthermore, we show that good approximations can be obtained numerically by sampling the considered area. Finally, we derive a method for normal computation on surfaces in discrete space.     

基于广义逆矩阵的B样条曲线节点消去算法研究

为了能运用广义逆矩阵理论来研究B样条曲线的节点消去问题，以解决在B样条曲线曲面拟合过程中产生的冗余节点数据，提出了一种基于广义逆矩阵的B样条曲线节点消去算法，该算法首先利用广义逆矩阵在处理奇异性问题上的独特作用来获得B样条曲线的节点可以消去的充要条件；然后在此基础上，又提出了消去多个节点的算法，算法对每个可以消去的节点都可计算相应的广义逆矩阵，而且仅进行一次矩阵的相乘即可得到由消去这个节点而产生的新的控制顶点和节点。实验表明，该算法的精度优于或近似于现有的Tiller算法，而时间效率则同于或近似于Tiller的算法。由于通过调整算法中的误差阈值，可以有效地控制消去节点后的曲线与原来曲线的误差，因此算法可以用于工程实践。     

Ribbon-based transfinite surfaces

One major issue in CAGD is to model complex objects using free-form surfaces of general topology. A natural approach is curvenet-based design, where designers directly create and modify feature curves. These are interpolated by smoothly connected, multi-sided patches, which can be represented by transfinite surfaces, defined as a combination of side interpolants or ribbons. A ribbon embeds Hermite data, i.e., prescribed positional and cross-derivative functions along boundary curves.The paper focuses on two transfinite schemes: the first is an enhanced and extended variant of a multi-sided generalization of the classical Coons patch (Várady et al., 2011); the second one is based on a new concept of combining doubly curved composite ribbons, each one interpolating three adjacent sides. Main contributions include various ribbon parameterizations that surpass former methods in quality and computational efficiency. It is proven that these surfaces smoothly interpolate the prescribed ribbon data. Both formulations are based on non-regular convex polygonal domains and distance-based, rational blending functions. A few examples illustrate the results.     

Optimal path planning for automated dimensional inspection of free-form surfaces

Structural dimensional inspection is vital for the process monitoring, quality control, and fault diagnosis in the mass production of auto bodies. Comparing with the non-contact measurement, the high-precision five-axis measuring machine with the touch-trigger probe is a preferred choice for data collection. It can assist manufacturers in making accurate inspection quickly. As the increase of free-form surfaces and diverse surface orientations in product design, existing inspection approaches cannot capture some new critical features in the curvature of products in an efficient way. Therefore, we need to develop new path planning methods for automated dimensional inspection of free-form surfaces. This paper proposes an optimal path planning system for automated programming of measuring point inspection by incorporating probe rotations and effective collision detection. Specifically, the methodological contributions include: (i) a dynamic searching volume-based algorithm is developed to detect potential collisions in the local path between measurement points; (ii) a local path generation method is proposed with the integration of the probe trajectory and the stylus rotation. Then, the inspection time matrix is proposed to quantify the measuring time of diverse local paths; (iii) an optimization approach of the global inspection path for all critical points on the product is developed to minimize the total inspection time. A case study has been conducted on an auto body to verify the performance of the proposed method. Results show that the collision-free path for the free-form auto body could be generated automatically with off-line programming, and the proposed method produces about 40% fewer dummy points and needs 32% less movement time in the auto body inspection process.     

A generalized orthonormal basis for linear dynamical systems

In many areas of signal, system, and control theory, orthogonal functions play an important role in issues of analysis and design. In this paper, it is shown that there exist orthogonal functions that, in a natural way, are generated by stable linear dynamical systems and that compose an orthonormal basis for the signal space l₂ⁿ . To this end, use is made of balanced realizations of inner transfer functions. The orthogonal functions can be considered as generalizations of, for example, the pulse functions, Laguerre functions, and Kautz functions, and give rise to an alternative series expansion of rational transfer functions. It is shown how we can exploit these generalized basis functions to increase the speed of convergence in a series expansion, i.e., to obtain a good approximation by retaining only a finite number of expansion coefficients. Consequences for identification of expansion coefficients are analyzed, and a bound is formulated on the error that is made when approximating a system by a finite number of expansion coefficients     

Inner functions and a pseudo-singular-value decomposition in super-optimal H∞ control

The inner functions and pseudo-singular-value decomposition (PSVD) which arise in super optimal H^∞ control are studied. New properties of non-square inner matrices are derived and a structural inner matrix is defined as an inner matrix with no transmission zeros. The uniqueness properties of the PSVD are derived and structural inner functions are used to characterize particular PSVDs     

Representing images using nonorthogonal Haar-like bases

Efficient and compact representation of images is a fundamental problem in computer vision. In this paper, we propose methods that use Haar-like binary box functions to represent a single image or a set of images. A desirable property of these box functions is that their inner product operation with an image can be computed very efficiently. We propose two closely related novel subspace methods to model images: the non-orthogonal binary subspace (NBS) method and binary principal component analysis (B-PCA) algorithm. NBS is spanned directly by binary box functions and can be used for image representation, fast template matching and many other vision applications. B-PCA is a structure subspace that inherits the merits of both NBS (fast computation) and PCA (modeling data structure information). B-PCA base vectors are obtained by a novel PCA guided NBS method. We also show that BPCA base vectors are nearly orthogonal to each other. As a result, in the non-orthogonal vector decomposition process, the computationally intensive pseudo-inverse projection operator can be approximated by the direct dot product without causing significant distance distortion. Experiments on real image datasets show promising performance in image matching, reconstruction and recognition tasks with significant speed improvement.