Repairing Inconsistent Curve Networks on Non‐parallel Cross‐sections

In this work we present the first algorithm for restoring consistency between curve networks on non‐parallel cross‐sections. Our method addresses a critical but overlooked challenge in the reconstruction process from cross‐sections that stems from the fact that cross‐sectional slices are often generated independently of one another, such as in interactive volume segmentation. As a result, the curve networks on two non‐parallel slices may disagree where the slices intersect, which makes these cross‐sections an invalid input for surfacing. We propose a method that takes as input an arbitrary number of non‐parallel slices, each partitioned into two or more labels by a curve network, and outputs a modified set of curve networks on these slices that are guaranteed to be consistent. We formulate the task of restoring consistency while preserving the shape of input curves as a constrained optimization problem, and we propose an effective solution framework. We demonstrate our method on a data‐set of complex multi‐labeled input cross‐sections. Our technique efficiently produces consistent curve networks even in the presence of large errors.     

Building 3D surface networks from 2D curve networks with application to anatomical modeling

Constructing 3D surfaces that interpolate 2D curves defined on parallel planes is a fundamental problem in computer graphics with wide applications including modeling anatomical structures. Typically the problem is simplified so that the 2D curves partition each plane into only two materials (e.g., air versus tissue). Here we consider the general problem where each plane is partitioned by a curve network into multiple materials (e.g., air, cortex, cerebellum, etc.). We present a novel method that automatically constructs a surface network from curve networks with arbitrary topology and partitions an arbitrary number of materials. The surface network exactly interpolates the curve network on each plane and is guaranteed to be free of gaps or self-intersections. In addition, our method provides a flexible framework for user interaction so that the surface topology can be modified conveniently when necessary. As an application, we applied the method to build a high-resolution 3D model of the mouse brain from 2D anatomical boundaries defined on 350 tissue sections. The surface network accurately models the partitioning of the brain into 17 abutting anatomical regions with complex topology.     

基于BP神经网络的隐式曲线构造方法

隐式曲线与曲面是当前计算机图形学研究的热点之一。通过把BP神经网络与隐式曲线构造原理相结合，提出了一种构造隐式曲线的新方法，即首先由约束点构造神经网络的输入与输出，把描述物体边界曲线的隐式函数转化为显式函数；然后用BP神经网络对此显式函数进行逼近；最后由仿真曲面得到物体边界的拟合曲线。该新方法不同于传统的对显式函数的逼近方法，因为传统方法无法描述封闭的曲线；也不同于基于优化的拟合隐式曲线方法，因为它无须考虑函数的形式或多项式的次数。实验表明，该新方法有很强的物体边界描述能力和缺损修复能力，因而在物体边界重建、缺损图像复原等领域有一定的应用前景。     

一种任意三维实体网格模型的体积特征提取算法

体积在不同轴向上的分布是三维网格模型的重要几何特征。在分析三维模型数据结构的基础上，提出一种提取任意三维实体网格模型体积分布特征的算法。算法首先应用主元分析法确定模型的主轴方向，并将模型按主轴方向旋转至特定姿态，再以一组等距的平行平面从三个坐标轴方向对模型进行剖分处理，并利用平面简单多边形的带符号面积公式求取相应的截面面积，进而求得模型的沿不同轴向的体积分布特征。模型在三个坐标轴向上的体积分布描述了模型的几何特征。实验表明，算法程序运行稳定、快速，可用于提取具有任意几何和拓扑复杂性的各类实体模型的体积分布特征。     

Homotopic Morphing of Planar Curves

This paper presents an algorithm for morphing between closed, planar piecewise‐C¹ curves. The morph is guaranteed to be a regular homotopy, meaning that pinching will not occur in the intermediate curves. The algorithm is based on a novel convex characterization of the space of regular closed curves and a suitable symmetric length‐deviation energy. The intermediate curves constructed by the morphing algorithm are guaranteed to be regular due to the convexity and feasibility of the problem. We show that our method compares favorably with standard curve morphing techniques, and that these methods sometimes fail to produce a regular homotopy, and as a result produce an undesirable morph. We explore several applications and extensions of our approach, including morphing networks of curves with simple connectivity, morphing of curves with different turning numbers with minimal pinching, convex combination of several curves, and homotopic morphing of b‐spline curves via their control polygon.     

Fair Surface Reconstruction Using Quadratic Functionals

An algorithm for surface reconstruction from a polyhedron with arbitrary topology consisting of triangular faces is presented. The first variant of the algorithm constructs a curve network consisting of cubic Bézier curves meeting with tangent plane continuity at the vertices. This curve network is extended to a smooth surface by replacing each of the networks facets with a split patch consisting of three triangular Bézier patches. The remaining degrees of freedom of the curve network and the split patches are determined by minimizing a quadratic functional. This optimization process works either for the curve network and the split patches separately or in one simultaneous step. The second variant of our algorithm is based on the construction of an optimized curve network with higher continuity. Examples demonstrate the quality of the different methods.     

Generation of Discrete Bicubic G1 B-Spline Ship Hullform Surfaces from a Given Curve Network Using Virtual Iso-Parametric Curves

We propose a method that automatically generates discrete bicubic G1 continuous B-spline surfaces that interpolate the curve network of a ship hullform. First, the curves in the network are classified into two types: boundary curves and "reference curves". The boundary curves correspond to a set of rectangular (or triangular) topological type that can be represented with tensor-product (or degenerate) B-spline surface patches. Next, in the interior of the patches, surface fitting points and cross boundary derivatives are estimated from the reference curves by constructing "virtual" isoparametric curves. Finally, a discrete G1 continuous B-spline surface is generated by a surface fitting algorithm. Several smooth ship hullform surfaces generated from curve networks corresponding to actual ship hullforms demonstrate the quality of the method.     

Prototype Modeling from Sketched Silhouettes based on Convolution Surfaces

This paper presents a hybrid method for creating three‐dimensional shapes by sketching silhouette curves. Given a silhouette curve, we approximate its medial axis as a set of line segments, and convolve a linearly weighted kernel along each segment. By summing the fields of all segments, an analytical convolution surface is obtained. The resulting generic shape has circular cross‐section, but can be conveniently modified via sketched profile or shape parameters of a spatial transform. New components can be similarly designed by sketching on different projection planes. The convolution surface model lends itself to smooth merging between the overlapping components. Our method overcomes several limitations of previous sketched‐based systems, including designing objects of arbitrary genus, objects with semi‐sharp features, and the ability to easily generate variants of shapes.     

Incremental Labelling of Voronoi Vertices for Shape Reconstruction

We present an incremental Voronoi vertex labelling algorithm for approximating contours, medial axes and dominant points (high curvature points) from 2D point sets. Though there exist many number of algorithms for reconstructing curves, medial axes or dominant points, a unified framework capable of approximating all the three in one place from points is missing in the literature. Our algorithm estimates the normals at each sample point through poles (farthest Voronoi vertices of a sample point) and uses the estimated normals and the corresponding tangents to determine the spatial locations (inner or outer) of the Voronoi vertices with respect to the original curve. The vertex classification helps to construct a piece‐wise linear approximation to the object boundary. We provide a theoretical analysis of the algorithm for points non‐uniformly (ε‐sampling) sampled from simple, closed, concave and smooth curves. The proposed framework has been thoroughly evaluated for its usefulness using various test data. Results indicate that even sparsely and non‐uniformly sampled curves with outliers or collection of curves are faithfully reconstructed by the proposed algorithm.     

Information entropy-based viewpoint planning for 3-D object reconstruction

In this paper, we present an information entropy-based viewpoint-planning approach for reconstruction of freeform surfaces of three-dimensional objects. To achieve the reconstruction, the object is first sliced into a series of cross section curves, with each curve to be reconstructed by a closed B-spline curve. In the framework of Bayesian statistics, we propose an improved Bayesian information criterion (BIC) for determining the B-spline model complexity. Then, we analyze the uncertainty of the model using entropy as the measurement. Based on this analysis, we predict the information gain for each cross section curve for the next measurement. After predicting the information gain of each curve, we obtain the information change for all the B-spline models. This information gain is then mapped into the view space. The viewpoint that contains maximal information gain about the object is selected as the next best view. Experimental results show successful implementation of our view planning method for digitization and reconstruction of freeform objects.     

基于径向基函数网络的隐式曲线

将径向基函数网络与隐式曲线构造原理相结合,提出了构造隐式曲线的新方法,即首先由约束点构造神经网络的输入与输出,把描述物体边界曲线的隐式函数转化为显式函数,然后用径向基函数网络对此显式函数进行逼近,最后由神经网络的仿真曲面得到物体边界的拟合曲线．实验表明,基于径向基函数网络的隐式曲线具有很强的物体边界描述能力和缺损修复能力．     

Spiral刺绣针法的路径生成算法

Spiral刺绣针法是一种重要的刺绣针法．首先将待刺绣的区域划分成若干能够生成连续螺旋线的环状子区域，然后将这些子区域组织成一个二叉树结构，采用一个递归过程来连接各个子区域内的螺旋线。最终形成Spiral针法路径．文中算法生成的路径能够由内向外以等距的螺旋线填充任意形状多边形的连通域，并且螺旋线的形状与区域的边界相似．实验结果表明，该算法能获得较好的刺绣效果．     

Geometric modelling of drawbeads using vertical section sweeping

This paper presents a swept surface for the geometric model of drawbeads mounted on curved surfaces. Vertical section sweeping is used for the swept surface. The section curves are the cross sections of the drawbeads and the shapes of the section curves are variable. Also, the section planes are normal to the projection of the drawbead curve along the die opening direction. This paper presents a scheme for computing the variable vertical section curves and the smooth endings for the swept surface of a drawbead. The geometric model presented has a no-undercut shape in the die opening direction and easily represents the smooth ending at ends of drawbeads.     

Using simple decomposition for smoothing and feature pointdetection of noisy digital curves

This correspondence presents an algorithm for smoothed polygonal approximation of noisy digital planar curves, and feature point detection. The resulting smoothed polygonal representation preserves the signs of the curvature function of the curve. The algorithm is based on a simple decomposition of noisy digital curves into a minimal number of convex and concave sections. The location of each separation point is optimized, yielding the minimal possible distance between the smoothed approximation and the original curve. Curve points within a convex (concave) section are discarded if their angle signs do not agree with the section sign, and if the resulted deviations from the curve are less than a threshold ε, which is derived automatically. Inflection points are curve points between pairs of convex-concave sections, and cusps are curve points between pairs of convex-convex or concave-concave sections. Corners and points of local minimal curvature are detected by applying the algorithm to respective total curvature graphs. The detection of the feature points is based on properties of pairs of sections that are determined in an adaptive manner, rather than on properties of single points that are based on a fixed-size neighborhood. The detection is therefore reliable and robust. Complexity analysis and experimental results are presented     

密集堆叠下的高相似度木块横截面检测

快速有效地检测和获取木块横截面信息,是提升木块生产交易效率的关键。由于木块往往被密集堆叠、木块横截面相似度高且边界不明显,给检测木块横截面信息带来了较大的挑战。针对密集堆叠下的高相似度木块横截面检测困难,本文提出了简单高效的Wood R-CNN网络模型,通过改进模型的损失函数和非极大值抑制算法来提升检测精度,简化网络结构和改进特征金字塔网络来保证检测速度。实验证明:该模型可在密集堆叠情况下精确地检测高相似度木块横截面,检测速度较快且鲁棒性良好,可实际运用于木块生产和交易中。     

反求工程中扫描曲面特征的提取

根据扫描曲面的定义，本文提出了一种基于点云切片数据的扫描曲面特征的提取方法。首先，由平行且过扫描面特征的切片点云数据获取扫描轨迹曲线；接着，由垂直于扫描轨迹线的切片点云数据获得截面轮廓线；最后，由扫描轨迹曲线和截面轮廓线即可确定扫描面特征。本文算法已在UG／OPEN上实现，并用实例证明了该方法的正确性和可行性
性。     

Curve interpolation in recursively generated B-spline surfaces over arbitrary topology

Recursive subdivision is receiving a great deal of attention in the definition of B-spline surfaces over arbitrary topology. The technique has recently been extended to generate interpolating surfaces with given normal vectors at the interpolated vertices. This paper describes an algorithm to generate recursive subdivision surfaces that interpolate B-spline curves. The control polygon of each curve is defined by a path of vertices of the polyhedral network describing the surface. The method consists of applying a one-step subdivision of the initial network and modifying the topology in the neighborhood of the vertices generated from the control polygons. Subsequent subdivisions of the modified network generate sequences of polygons each of which converges to a curve interpolated by the limit surface. In the case of regular networks, the method can be reduced to a knot insertion process.     

Surface Patches from Unorganized Space Curves

Recent 3D sketch tools produce networks of three‐space curves that suggest the contours of shapes. The shapes may be non‐manifold, closed three‐dimensional, open two‐dimensional, or mixed. We describe a system that automatically generates intuitively appealing piecewise‐smooth surfaces from such a curve network, and an intelligent user interface for modifying the automatically chosen surface patches. Both the automatic and the semi‐automatic parts of the system use a linear algebra representation of the set of surface patches to track the topology. On complicated inputs from ILoveSketch [ [BBS08] ], our system allows the user to build the desired surface with just a few mouse‐clicks.     

Adapting Feature Curve Networks to a Prescribed Scale

Feature curves on surface meshes are usually defined solely based on local shape properties such as dihedral angles and principal curvatures. From the application perspective, however, the meaningfulness of a network of feature curves also depends on a global scale parameter that takes the distance between feature curves into account, i.e., on a coarse scale, nearby feature curves should be merged or suppressed if the surface region between them is not representable at the given scale/resolution. In this paper, we propose a computational approach to the intuitive notion of scale conforming feature curve networks where the density of feature curves on the surface adapts to a global scale parameter. We present a constrained global optimization algorithm that computes scale conforming feature curve networks by eliminating curve segments that represent surface features, which are not compatible to the prescribed scale. To demonstrate the usefulness of our approach we apply isotropic and anisotropic remeshing schemes that take our feature curve networks as input. For a number of example meshes, we thus generate high quality shape approximations at various levels of detail.     

Fast Constrained Surface Extraction by Minimal Paths

In this paper we consider a new approach for single object segmentation in 3D images. Our method improves the classical geodesic active surface model. It greatly simplifies the model initialization and naturally avoids local minima by incorporating user extra information into the segmentation process. The initialization procedure is reduced to introducing 3D curves into the image. These curves are supposed to belong to the surface to extract and thus, also constitute user given information. Hence, our model finds a surface that has these curves as boundary conditions and that minimizes the integral of a potential function that corresponds to the image features. Our goal is achieved by using globally minimal paths. We approximate the surface to extract by a discrete network of paths. Furthermore, an interpolation method is used to build a mesh or an implicit representation based on the information retrieved from the network of paths. Our paper describes a fast construction obtained by exploiting the Fast Marching algorithm and a fast analytical interpolation method. Moreover, a Level set method can be used to refine the segmentation when higher accuracy is required. The algorithm has been successfully applied to 3D medical images and synthetic images.