Accurate GPU-accelerated surface integrals for moment computation

We present algorithms for computing accurate moments of solid models that are represented using multiple trimmed NURBS surfaces and triangles. Our algorithms make use of programmable Graphics Processing Units (GPUs) to accelerate the moment computations. For NURBS surfaces, we evaluate the surface coordinates and normals accurately, with theoretical bounds, using our GPU NURBS evaluator. We have developed a framework that makes use of this data to evaluate surface integrals of trimmed NURBS surfaces in real time. Since typical solid models also contain flat planes that are usually tessellated into triangles, our framework also includes GPU acceleration of the moment contributions of such flat faces. Using our framework, we can compute volume and moments of solid models with theoretical guarantees. Our algorithms support local geometry changes, which is useful for providing interactive feedback to the designer while the solid model is being designed. We can compute the center of mass and check for stability of the solid model interactively. Other applications of such real-time moment computation include deformation modeling, animation, and physically based simulations.     

Performing Efficient NURBS Modeling Operations on the GPU

We present algorithms for evaluating and performing modeling operations on NURBS surfaces using the programmable fragment processor on the Graphics Processing Unit (GPU). We extend our GPU-based NURBS evaluator that evaluates NURBS surfaces to compute exact normals for either standard or rational B-spline surfaces for use in rendering and geometric modeling. We build on these calculations in our new GPU algorithms to perform standard modeling operations such as inverse evaluations, ray intersections, and surface-surface intersections on the GPU. Our modeling algorithms run in real time, enabling the user to sketch on the actual surface to create new features. In addition, the designer can edit the surface by interactively trimming it without the need for retessellation. Our GPU-accelerated algorithm to perform surface-surface intersection operations with NURBS surfaces can output intersection curves in the model space as well as in the parametric spaces of both the intersecting surfaces at interactive rates. We also extend our surface-surface intersection algorithm to evaluate self-intersections in NURBS surfaces.     

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.     

gProximity: Hierarchical GPU‐based Operations for Collision and Distance Queries

We present novel parallel algorithms for collision detection and separation distance computation for rigid and deformable models that exploit the computational capabilities of many‐core GPUs. Our approach uses thread and data parallelism to perform fast hierarchy construction, updating, and traversal using tight‐fitting bounding volumes such as oriented bounding boxes (OBB) and rectangular swept spheres (RSS). We also describe efficient algorithms to compute a linear bounding volume hierarchy (LBVH) and update them using refitting methods. Moreover, we show that tight‐fitting bounding volume hierarchies offer improved performance on GPU‐like throughput architectures. We use our algorithms to perform discrete and continuous collision detection including self‐collisions, as well as separation distance computation between non‐overlapping models. In practice, our approach (gProximity) can perform these queries in a few milliseconds on a PC with NVIDIA GTX 285 card on models composed of tens or hundreds of thousands of triangles used in cloth simulation, surgical simulation, virtual prototyping and N‐body simulation. Moreover, we observe more than an order of magnitude performance improvement over prior GPU‐based algorithms.     

Interactive display of large NURBS models

We present algorithms for interactive rendering of large-scale NURBS models. The algorithms convert the NURBS surfaces to Bezier surfaces, tessellate each Bezier surface into triangles, and render them using the triangle-rendering capabilities common to current graphics systems. We present algorithms for computing tight bounds on surface properties in order to generate high quality tessellation of Bezier surfaces. We introduce enhanced visibility determination techniques and present methods to make efficient use of coherence between successive frames. In addition, we also discuss issues in parallelization of these techniques. The algorithm also avoids polygonization anomalies like cracks. Our algorithms work well in practice and, on high-end graphics systems, are able to display models described using thousands of Bezier surfaces at interactive frame rates     

Voxelized Minkowski sum computation on the GPU with robust culling

We present a new approach for computing the voxelized Minkowski sum (excluding any enclosed voids) of two polyhedral objects using programmable Graphics Processing Units (GPUs). We first cull out surface primitives that will not contribute to the final boundary of the Minkowski sum, analyzing and adaptively bounding the rounding errors of the culling algorithm to solve the floating point error problem. The remaining surface primitives are then rendered to depth textures along six orthogonal directions to generate an initial solid voxelization of the Minkowski sum. Finally we employ fast flood fill to find all the outside voxels. We generate both solid and surface voxelizations of Minkowski sums without enclosed voids and support high volumetric resolution of 1024³ with low video memory cost. The whole algorithm runs on the GPU and is at least one order of magnitude faster than existing boundary representation (B-rep) based algorithms. It avoids the large number of 3D Boolean operations needed in most existing algorithms and is easy to implement. The voxelized Minkowski sums can be used in a variety of applications including motion planning and penetration depth computation.     

GPU-accelerated Hausdorff distance computation between dynamic deformable NURBS surfaces

We present a parallel GPU-accelerated algorithm for computing the directed Hausdorff distance from one NURBS surface to another, within a bound. We make use of axis-aligned bounding-box hierarchies that bound the NURBS surfaces to accelerate the computations. We dynamically construct as well as traverse the bounding-box hierarchies for the NURBS surfaces using operations that are optimized for the GPU. To compute the Hausdorff distance, we traverse this hierarchy after culling bounding-box pairs that do not contribute to the Hausdorff distance. Our contribution includes two-sided culling tests that can be performed in parallel using the GPU. The culling, based on the minimum and maximum distance ranges between the bounding boxes, eliminates bounding-box pairs from both surfaces that do not contribute to the Hausdorff distance simultaneously. We calculate accuracy bounds for our computed Hausdorff distance based on the curvature of the surfaces. Our algorithm runs in real-time with very small guaranteed error bounds for complex NURBS surfaces. Since we dynamically construct our bounding-box hierarchy, our algorithm can be used to interactively compute the Hausdorff distance for models made of dynamic deformable surfaces.     

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.     

High Performance GPU‐based Proximity Queries using Distance Fields

Proximity queries such as closest point computation and collision detection have many applications in computer graphics, including computer animation, physics‐based modelling, augmented and virtual reality. We present efficient algorithms for proximity queries between a closed rigid object and an arbitrary, possibly deformable, polygonal mesh. Using graphics hardware to densely sample the distance field of the rigid object over the arbitrary mesh, we compute minimal proximity and collision response information on the graphics processing unit (GPU) using blending and depth buffering, as well as parallel reduction techniques, thus minimizing the readback bottleneck. Although limited to image‐space resolution, our algorithm provides high and steady performance when compared with other similar algorithms. Proximity queries between arbitrary meshes with hundreds of thousands of triangles and detailed distance fields of rigid objects are computed in a few milliseconds at high‐sampling resolution, even in situations with large overlap.     

Interactive rendering of NURBS surfaces

NURBS (Non-uniform rational B-splines) surfaces are one of the most useful primitives employed for high quality modeling in CAD/CAM tools and graphics software. Since direct evaluation of NURBS surfaces on the GPU is a highly complex task, the usual approach for rendering NURBS is to perform the conversion into Bézier surfaces on the CPU, and then evaluate and tessellate them on the GPU. In this paper we present a new proposal for rendering NURBS surfaces directly on the GPU in order to achieve interactive and real-time rendering. Our proposal, Rendering Pipeline for NURBS Surfaces (RPNS), is based on a new primitive KSQuad that uses a regular and flexible processing of NURBS surfaces, while maintaining their main geometric properties to achieve real-time rendering. RPNS performs an efficient adaptive discretization to fine tune the density of primitives needed to avoid cracks and holes in the final image, applying an efficient non-recursive evaluation of the basis function on the GPU. An implementation of RPNS using current GPUs is presented, achieving real-time rendering rates of complex parametric models. Our experimental tests show a performance several orders of magnitude higher than traditional approximations based on NURBS to Bézier conversion.     

TightCCD: Efficient and Robust Continuous Collision Detection using Tight Error Bounds

http://gamma.cs.unc.edu/BSC/ We present a realtime and reliable continuous collision detection (CCD) algorithm between triangulated models that exploits the floating point hardware capability of current CPUs and GPUs. Our formulation is based on Bernstein Sign Classification that takes advantage of the geometry properties of Bernstein basis and Bézier curves to perform Boolean collision queries. We derive tight numerical error bounds on the computations and employ those bounds to design an accurate algorithm using finite‐precision arithmetic. Compared with prior floatingpoint CCD algorithms, our approach eliminates all the false negatives and 90–95% of the false positives. We integrated our algorithm (TightCCD) with physically‐based simulation system and observe speedups in collision queries of 5–15X compared with prior reliable CCD algorithms. Furthermore, we demonstrate its benefits in terms of improving the performance or robustness of cloth simulation systems.     

Efficient Image‐Based Proximity Queries with Object‐Space Precision

We present an efficient algorithm for object‐space proximity queries between multiple deformable triangular meshes. Our approach uses the rasterization capabilities of the GPU to produce an image‐space representation of the vertices. Using this image‐space representation, inter‐object vertex‐triangle distances and closest points lying under a user‐defined threshold are computed in parallel by conservative rasterization of bounding primitives and sorted using atomic operations. We additionally introduce a similar technique to detect penetrating vertices. We show how mechanisms of modern GPUs such as mipmapping, Early‐Z and Early‐Stencil culling can optimize the performance of our method. Our algorithm is able to compute dense proximity information for complex scenes made of more than a hundred thousand triangles in real time, outperforming a CPU implementation based on bounding volume hierarchies by more than an order of magnitude.     

Registering multiple range images based on distance metric of surface-to-surface

1 Introduction In recent years, there has been growing interest in the range sensing techniques for building 3D computer models of real-world objects and scenes without requiring hu-mans to manually produce these models using laborious and error-prone CAD-based approaches. Using range sensors, users are able to capture 3D range images of objects from different viewpoints that may be combined to form the final model of the object or scene[1]. These models then may be used for a variety of app…     

Efficient Hausdorff Distance computation for freeform geometric models in close proximity

We present an interactive-speed algorithm for computing the Hausdorff Distance (HD) between two freeform geometric models represented with NURBS surfaces. The algorithm is based on an effective technique for matching a surface patch from one model to the corresponding nearby surface patch on the other model. To facilitate the matching procedure, we employ a bounding volume hierarchy (BVH) for freeform NURBS surfaces, which provides a hierarchy of Coons patches and bilinear surfaces approximating the NURBS surfaces (Kim et al., 2011 [1]). Comparing the local HD upper bound against a global HD lower bound, we can eliminate the majority of redundant surface patches from further consideration. The resulting algorithm and the associated data structures are considerably simpler than the previous BVH-based HD algorithms. As a result, we can compute the HD of two freeform geometric models efficiently and robustly even when the two models are in close proximity. We demonstrate the effectiveness of our approach using several experimental results.     

Artifact analysis on B-splines, box-splines and other surfaces defined by quadrilateral polyhedra

When using NURBS or subdivision surfaces as a design tool in engineering applications, designers face certain challenges. One of these is the presence of artifacts. An artifact is a feature of the surface that cannot be avoided by movement of control points by the designer. This implies that the surface contains spatial frequencies greater than one cycle per two control points. These are seen as ripples in the surface and are found in NURBS and subdivision surfaces and potentially in all surfaces specified in terms of polyhedrons of control points.Ideally, this difference between designer intent and what emerges as a surface should be eliminated. The first step to achieving this is by understanding and quantifying the artifact observed in the surface.We present methods for analysing the magnitude of artifacts in a surface defined by a quadrilateral control mesh. We use the subdivision process as a tool for analysis. Our results provide a measure of surface artifacts with respect to initial control point sampling for all B-Splines, quadrilateral box-spline surfaces and regular regions of subdivision surfaces. We use four subdivision schemes as working examples: the three box-spline subdivision schemes, Catmull-Clark (cubic B-spline), 4-3, 4-8; and Kobbelt?s interpolating scheme.     

Efficient registration of NURBS geometry

The paper presents an implementation of free-form surface registration in relation to inspection of engineering components, defined as NURBS. Registration is principally performed through the Iterative Closest Point (ICP) method. The time-critical step in ICP was found to be the determination of the closest points on NURBS to a given point in space. Significant speed improvements were achieved through the adoption of a dual surface representation, involving approximation of NURBS entities by a polyhedral mesh. A criterion for sufficient polyhedral approximation was derived and implemented, producing encouraging results. Original solutions are suggested in order to further improve the computational speed. Extensive testing has been carried out, showing that the proposed registration method handles a full six degrees of freedom and achieves global convergence. Performance of the implemented algorithms is discussed with reference to registration of a turbine blade airfoil.     

基于流的实时碰撞检测算法

实时碰撞检测是计算机图形应用中不可或缺的问题之一,复杂物体间的实时碰撞检测至今仍未能得以很好的解决.高性能可编程图形硬件的出现,正在改变着通用计算仅能由CPU完成的传统观念.探索性地采用了可编程图形硬件来解决复杂物体间的实时碰撞检测问题.通过将两个任意物体间的碰撞检测计算映射到图形硬件以有效利用图形硬件的并行架构,由实时绘制过程快速产生碰撞检测结果.为此,算法首先将碰撞检测问题转化为一组线段集合与三角形的求交问题,以实现碰撞检测算法向可编程图形硬件的迁移.在对算法复杂度进行理性分析的基础上,给出了两种有效的优化技术以提升算法效率.实验结果表明,与现有的图像空间碰撞检测算法相比,该算法在效率、精确性和实用性方面具有明显优势.     

Efficient and accurate B-rep generation of low degree sculptured solids using exact arithmetic: II—computation

We present efficient algorithms for exact boundary computation on low degree sculptured CSG solids using exact arithmetic. These include algorithms for computing the intersection curves of low-degree trimmed parametric surfaces, decomposing them into multiple components for efficient point location queries inside the trimmed regions, and computing the boundary of the resulting solid using topological information and component classification tests. We also employ a number of previously developed algorithms such as algebraic curve classification and multivariate Sturm sequences. We present some results from a preliminary implementation of our approach. This paper follows a previous paper which described the representations used in our approach.