Offsets of curves on rational B-spline surfaces

The construction of offset curves is an important problem encountered often in design processes and in interrogation of geometric models. In this paper the problem of construction of offsets of curves lying on the same parametric surface is addressed. A novel algorithm is introduced, whose main feature is the use of geodesic paths to determine points of the offset. The offset is then approximated in the underlying surface parameter space by B-splines interpolating data points obtained by traveling a known distance along the geodesics departing from corresponding points of the progenitor in a direction perpendicular to the latter. A comprehensive error checking scheme has been devised allowing adaptive improvement of the approximation of the offset. The applicability of the algorithm is demonstrated by number of numerical examples.     

Trimming local and global self-intersections in offset curves/surfaces using distance maps

A robust and efficient algorithm for trimming both local and global self-intersections in offset curves and surfaces is presented. Our scheme is based on the derivation of a rational distance map between the original curve or surface and its offset. By solving a bivariate polynomial equation for an offset curve or a system of three polynomial equations for an offset surface, all local and global self-intersection regions in offset curves or surfaces can be detected. The zero-set of polynomial equation(s) corresponds to the self-intersection regions. These regions are trimmed by projecting the zero-set into an appropriate parameter space. The projection operation simplifies the analysis of the zero-set, which makes the proposed algorithm numerically stable and efficient. Furthermore, in a post-processing step, a numerical marching method is employed, which provides a highly precise scheme for self-intersection elimination in both offset curves and surfaces. The effectiveness of our approach is demonstrated using several experimental results.     

GPU-based offset surface computation using point samples

We present an efficient algorithm to perform approximate offsetting operations on geometric models using GPUs. Our approach approximates the boundary of an object with point samples and computes the offset by merging the balls centered at these points. The underlying approach uses Layered Depth Images (LDI) to organize the samples into structured points and performs parallel computations using multiple cores. We use spatial hashing to accelerate intersection queries and balance the workload among various cores. Furthermore, the problem of offsetting with a large distance is decomposed into successive offsetting using smaller distances. We derive bounds on the accuracy of offset computation as a function of the sampling rate of LDI and offset distance. In practice, our GPU-based algorithm can accurately compute offsets of models represented using hundreds of thousands of points in a few seconds on a GeForce GTX 580 GPU. We observe more than 100 times speedup over prior serial CPU-based approximate offset computation algorithms.     

Curvature-aware adaptive re-sampling for point-sampled geometry

With the emergence of large-scale point-sampled geometry acquired by high-resolution 3D scanning devices, it has become increasingly important to develop efficient algorithms for processing such models which have abundant geometric details and complex topology in general. As a preprocessing step, surface simplification is important and necessary for the subsequent operations and geometric processing. Owing to adaptive mean-shift clustering scheme, a curvature-aware adaptive re-sampling method is proposed for point-sampled geometry simplification. The generated sampling points are non-uniformly distributed and can account for the local geometric feature in a curvature aware manner, i.e. in the simplified model the sampling points are dense in the high curvature regions, and sparse in the low curvature regions. The proposed method has been implemented and demonstrated by several examples.     

A shape design system using volumetric implicit PDEs

Solid modeling based on partial differential equations (PDEs) can potentially unify both geometric constraints and functional requirements within a single design framework to model real-world objects via its explicit, direct integration with parametric geometry. In contrast, implicit functions indirectly define geometric objects as the level-set of underlying scalar fields. To maximize the modeling potential of PDE-based methodology, in this paper we tightly couple PDEs with volumetric implicit functions in order to achieve interactive, intuitive shape representation, manipulation, and deformation. In particular, the unified approach can reconstruct the PDE geometry of arbitrary topology from scattered data points or a set of sketch curves. We make use of elliptic PDEs for boundary value problems to define the volumetric implicit function. The proposed implicit PDE model has the capability to reconstruct a complete solid model from partial information and facilitates the direct manipulation of underlying volumetric datasets via sketch curves and iso-surface sculpting, deformation of arbitrary interior regions, as well as a set of CSG operations inside the working space. The prototype system that we have developed allows designers to interactively sketch the curve outlines of the object, define intensity values and gradient directions, and specify interpolatory points in the 3D working space. The governing implicit PDE treats these constraints as generalized boundary conditions to determine the unknown scalar intensity values over the entire working space. The implicit shape is reconstructed with specified intensity value accordingly and can be deformed using a set of sculpting toolkits. We use the finite-difference discretization and variational interpolating approach with the localized iterative solver for the numerical integration of our PDEs in order to accommodate the diversity of generalized boundary and additional constraints.     

A new constructive approach to constraint-based geometric design

In the paper, a new constructive approach to solving geometric constraints in 2-D space is presented. Constraints are employed on lines and points only, but more sophisticated geometric elements like Bézier curves and ellipses can also be constrained by mapping them onto auxiliary lines and points. The algorithm is based on local propagation, but first, the problem is transformed into a form that guarantees success of employing this simple technique. The most important steps are substitution of complex constraints with sets of simpler ones and insertion of redundant constraints by solving triangles and determining sums and differences of adjacent angles. In this way, various well-constrained problems with a few exceptions are solved, over-constrained scenes and input data contradictory to some well-known mathematical theorems are detected, and the algorithm is proved successful in many under-constrained cases as well.     

蒙太奇网格融合

三维物体融合是一种新的几何造型方法,它利用三维模型之间的剪贴操作从两个或多个现有的几何模型中光滑融合出新的几何模型.提出了一种基于局部调和映射的三维网格蒙太奇融合新方法.首先利用网格上的近似等距线算法来抽取出待融合区域,然后对两个待融合区域进行带内孔的调和映射参数化,最后通过拓扑合并和融合控制来实现网格的光滑融合.与原有的基于全局调和映射的融合方法相比,新方法的算法效率大幅度提升,求解时间不再随融合模型顶点数的增加而呈指数增长;减少了二维网格拓扑合并中奇异情况出现的概率,提高了算法的稳定性;被剪切网格的细节得到完整保留;消除了原算法对融合区域拓扑的限制.实验结果表明,此方法可以用来生成许多三维动画中的特殊夸张造型效果,在影视动画中具有应用价值.     

A method for solving mass point-in-covering problems for arbitrary coverings using GPU

Results of numerical experiments in solving mass problems of determining membership of a set of points in a set of arbitrary shapes covering a domain or intersecting with each other in a space of arbitrary dimension are discussed. The problems are solved using geometrical techniques on graphics processors. The proposed solution can outperform the fastest classical algorithms by a factor from 6 to 700 in terms of speed. As an example, the construction of grids for computations within a geophysical model of the Earth is used. Such problems are typical for all the numerical computations involving geometric modeling where coverings or triangulations are used or rendering problems are solved.     

Offset of curves on tessellated surfaces

Geodesic offset of curves on surfaces is an important and useful tool of computer aided design for applications such as generation of tool paths for NC machining and simulation of fibre path on tool surfaces in composites manufacturing. For many industrial and graphic applications, tessellation representation is used for curves and surfaces because of its simplicity in representation and for simpler and faster geometric operations. The paper presents an algorithm for computing offset of curves on tessellated surfaces. A curve on tessellation (COT) is represented as a sequence of 3D points, with each line segment of every two consecutive points lying exactly on the tessellation. With an incremental approach of the algorithm to compute offset COT, the final offset curve position is obtained through several intermediate offset curve positions. Each offset curve position is obtained by offsetting all the points of COT along the tessellation in such a way that all the line segments gets offset exactly along the faces of tessellation in which the line segments are contained. The algorithm, based entirely on tessellation representation, completely eliminates the formation of local self-intersections. Global self-intersections if any, are detected and corrected explicitly. Offset of both open and closed tessellated curves, either in a plane or on a tessellated surface, can be generated using the proposed approach. The computation of offset COT is very accurate within the tessellation tolerance.     

Integration of topology and shape optimization for design of structural components

This paper presents an integrated approach that supports the topology optimization and CAD-based shape optimization. The main contribution of the paper is using the geometric reconstruction technique that is mathematically sound and error bounded for creating solid models of the topologically optimized structures with smooth geometric boundary. This geometric reconstruction method extends the integration to 3-D applications. In addition, commercial Computer-Aided Design (CAD), finite element analysis (FEA), optimization, and application software tools are incorporated to support the integrated optimization process. The integration is carried out by first converting the geometry of the topologically optimized structure into smooth and parametric B-spline curves and surfaces. The B-spline curves and surfaces are then imported into a parametric CAD environment to build solid models of the structure. The control point movements of the B-spline curves or surfaces are defined as design variables for shape optimization, in which CAD-based design velocity field computations, design sensitivity analysis (DSA), and nonlinear programming are performed. Both 2-D plane stress and 3-D solid examples are presented to demonstrate the proposed approach. Received January 27, 2000 Communicated by J. Sobieski     

Exact and Robust (Self‐)Intersections for Polygonal Meshes

We present a new technique to implement operators that modify the topology of polygonal meshes at intersections and self‐intersections. Depending on the modification strategy, this effectively results in operators for Boolean combinations or for the construction of outer hulls that are suited for mesh repair tasks and accurate mesh‐based front tracking of deformable materials that split and merge. By combining an adaptive octree with nested binary space partitions (BSP), we can guarantee exactness (= correctness) and robustness (= completeness) of the algorithm while still achieving higher performance and less memory consumption than previous approaches. The efficiency and scalability in terms of runtime and memory is obtained by an operation localization scheme. We restrict the essential computations to those cells in the adaptive octree where intersections actually occur. Within those critical cells, we convert the input geometry into a plane‐based BSP‐representation which allows us to perform all computations exactly even with fixed precision arithmetics. We carefully analyze the precision requirements of the involved geometric data and predicates in order to guarantee correctness and show how minimal input mesh quantization can be used to safely rely on computations with standard floating point numbers. We properly evaluate our method with respect to precision, robustness, and efficiency.     

Implicit simplicial models for adaptive curve reconstruction

Parametric deformable models have been extensively and very successfully used for reconstructing free-form curves and surfaces, and for tracking nonrigid deformations, but they require previous knowledge of the topological type of the data, and good initial curve or surface estimates. With deformable models, it is also computationally expensive to check for and to prevent self-intersections while tracking deformations. The implicit simplicial models that we introduce in this paper are implicit curves and surfaces defined by piecewise linear functions. This representation allows for local deformations, control of the topological type, and prevention of self-intersections during deformations. As a first application, we also describe an algorithm for 2D curve reconstruction from unorganized sets of data points. The topology, the number of connected components, and the geometry of the data are all estimated using an adaptive space subdivision approach. The main four components of the algorithm are topology estimation, curve fitting, adaptive space subdivision, and mesh relaxation     

A generic lazy evaluation scheme for exact geometric computations

We present a generic C++ design to perform exact geometric computations efficiently using lazy evaluations. Exact geometric computations are critical for the robustness of geometric algorithms. Their efficiency is also important for many applications, hence the need for delaying the costly exact computations at run time until they are actually needed, if at all. Our approach is generic and extensible in the sense that it is possible to make it a library that users can apply to their own geometric objects and primitives. It involves techniques such as generic functor-adaptors, static and dynamic polymorphism, reference counting for the management of directed acyclic graphs, and exception handling for triggering exact computations when needed. It also relies on multi-precision arithmetic as well as interval arithmetic. We apply our approach to the whole geometry kernel of Cgal.     

Fast hierarchical animated object decomposition using approximately invariant signature

In this paper, we introduce a novel method to hierarchically decompose the animated 3d object efficiently by utilizing high-dimensional and multi-scale geometric information. The key idea is to treat the animated surface sequences as a whole and extract the near-rigid components from it. Our approach firstly detects a set of the multi-scale feature points on the animated object and computes approximately invariant signature vectors for these points. Then, exploiting both the geometric attributes and the local signature vector of each point (vertex) of the animated object, all the points (vertices) of the animated object can be clustered efficiently using a GPU-accelerated mean shift clustering algorithm. To refine the decomposition boundaries, the initially-generated boundaries of the animated object can be further improved by applying a boundary refinement technique based on Gaussian Mixture Models (GMMs). Furthermore, we propose a hierarchical decomposition technique using a topology merging strategy without introducing additional computations.     

Signed algebraic level sets on NURBS surfaces and implicit Boolean compositions for isogeometric CAD–CAE integration

Boundary-representation (B-rep) geometrical models, often mathematically represented using Non-Uniform Rational B-Spline (NURBS) surfaces, are the starting point for complex downstream product life-cycle evaluations including Computer-Aided Engineering (CAE). Boolean operations during B-rep model generation require surface intersection computations to describe the composed entity. However, for parametric NURBS surfaces, intersection operations are non-trivial and typically carried out numerically. The numerical intersection computations introduce challenges relating to the accuracy of the resulting representation, efficiency with which the computation is carried out, and robustness of the result to small variations in geometry. Often, for downstream CAE evaluations, an implicit, procedural knowledge of the Boolean operations between the composed objects that can resolve point containment queries (exact to the original NURBS bounding surfaces) maybe sufficient during quadrature. However, common point containment queries on B-rep models are numerical, iterative and relatively expensive. Thus, the first goal of the present paper is to describe a purely algebraic, and therefore non-iterative, approach to carrying out point containment queries on complex B-rep models built using low-degree NURBS surfaces. For CAE operations, the boundary representation of B-rep solids is, in general, not convenient and as a result, the B-rep model is converted to a meshed volumetric approximation. The major challenges to such a conversion include capturing the geometric features accurately when constructing the secondary (meshed) representation, apart from the efficiency of carrying out such a mesh generation step repeatedly as the geometric shape evolves. Thus, an ideal analysis procedure would operate directly on B-rep CAD models, without needing a secondary mesh, and would procedurally unify the geometric operations during CAD as well as CAE stages. Therefore, the second and broader goal of the present paper is to demonstrate CAD–CAE integration using signed algebraic level set operations directly on B-rep models by embedding or immersing the bounding surfaces within a discretized domain while preserving the geometric accuracy of the surfaces exact to the original NURBS representation during analysis.     

Spectral moving removal of non-isolated surface outlier clusters

In this paper, we propose a new algorithm for the fast removal of non-isolated surface outlier clusters. It consists of three basic components: (a) an intrinsic metric for detecting outliers on the basis of minimum variance principle; (b) bi-means clustering of a normalized histogram; (c) surface propagation for a geometric coherence check. The unique contributions of our approach include (a) a new idea of identifying non-isolated outlier clusters and linking the local spectral property to a global outlier removal process; (b) a modified data clustering scheme with a geometric coherence check. In comparison with existing algorithms, our algorithm is evaluated in terms of the quality and computational cost of outlier removal. Numerical experiments indicate the effectiveness of our approach in the aspects of convergence, accuracy, time and space efficiency.     

An iterative/subdivision hybrid algorithm for?curve/curve?intersection

The problem of finding all intersections between two space curves is one of the fundamental problems in computer-aided geometric design and computational geometry. This article proposes a new iterative/subdivision hybrid algorithm for this problem. We use a test based on Kantorovich’s theorem to detect the starting point from which Newton’s method converges quadratically and a subdivision scheme to exclude certain regions that do not contain any intersections. Our algorithm is guaranteed to detect all intersections in the domain for nondegenerate and non-ill-posed cases.     

Shape registration in implicit spaces using information theory and free form deformations

We present a novel, variational and statistical approach for shape registration. Shapes of interest are implicitly embedded in a higher-dimensional space of distance transforms. In this implicit embedding space, registration is formulated in a hierarchical manner: the mutual information criterion supports various transformation models and is optimized to perform global registration; then, a B-spline-based incremental free form deformations (IFFD) model is used to minimize a sum-of-squared-differences (SSD) measure and further recover a dense local nonrigid registration field. The key advantage of such framework is twofold: 1) it naturally deals with shapes of arbitrary dimension (2D, 3D, or higher) and arbitrary topology (multiple parts, closed/open) and 2) it preserves shape topology during local deformation and produces local registration fields that are smooth, continuous, and establish one-to-one correspondences. Its invariance to initial conditions is evaluated through empirical validation, and various hard 2D/3D geometric shape registration examples are used to show its robustness to noise, severe occlusion, and missing parts. We demonstrate the power of the proposed framework using two applications: one for statistical modeling of anatomical structures, another for 3D face scan registration and expression tracking. We also compare the performance of our algorithm with that of several other well-known shape registration algorithms.     

Partitioning and Handling Massive Models for Interactive Collision Detection

We describe an approach for interactive collision detection and proximity computations on massive models composed of millions of geometric primitives. We address issues related to interactive data access and processing in a large geometric database, which may not fit into main memory of typical desktop workstations or computers. We present a new algorithm using overlap graphs for localizing the "regions of interest" within a massive model, thereby reducing runtime memory requirements. The overlap graph is computed off-line, pre-processed using graph partitioning algorithms, and modified on the fly as needed. At run time, we traverse localized sub-graphs to check the corresponding geometry for proximity and pre-fetch geometry and auxiliary data structures. To perform interactive proximity queries, we use bounding-volume hierarchies and take advantage of spatial and temporal coherence. Based on the proposed algorithms, we have developed a system called IMMPACT and used it for interaction with a CAD model of a power plant consisting of over 15 million triangles. We are able to perform a number of proximity queries in real-time on such a model. In terms of model complexity and application to large models, we have improved the performance of interactive collision detection and proximity computation algorithms by an order of magnitude.