基于DEM格网的改进型A*路径搜索算法

为解决DEM格网上的路径搜索问题,分析了DEM格网和道路拓扑网络的共性与区别,并结合DEM格网的特点对比了Dijkstra算法和A*算法的优缺点,提出了基于DEM格网的改进型A*路径搜索算法。该算法充分考虑DEM格网上的路径可达条件,采用移动窗口法获取搜索网格候选集,并根据地理空间分布特征选取A*算法的估价函数,同时引入贪婪准则缩小搜索范围,降低问题复杂度。结合实例对算法进行了实验分析,验证结果表明了该算法的可行性和有效性。     

A three-dimensional numerical manifold method based on tetrahedral meshes

A three-dimensional NMM based on tetrahedral meshes is developed in this paper. First, the displacement functions of manifold elements are formulated by the partition of unity function. Then, the global equilibrium equations for three-dimensional elasto-statics problem are established by minimizing the total potential energy. The stiffness matrix, loading matrix, displacement resistance matrix are derived for program coding. Thereafter, the computational cost of the global stiffness matrix in the NMM is discussed and compared with that in the classical finite element techniques. Finally, two typical examples are investigated to demonstrate the validity of the proposed method. The results indicate that an enough accuracy of approximation will be obtained with decreasing size of the mathematical mesh. The proposed method can be used as potentially powerful tool for three-dimensional structural analysis.     

Automatic generation of tetrahedral meshes from medical images

A new tetrahedral meshing algorithm from the series of medical images is proposed. Sectional contours are extracted from medical images, and by the use of correspondence, tiling, and branching process, the side surfaces between sections are triangulated in addition to the triangulation on each section. As for the mesh generation for an object between two sections, an advancing front algorithm is employed to generate tetrahedral elements by using basic operators. Sample meshes are constructed from medical images for finite element analysis of biomechanical models.     

Existence and construction of Hamiltonian paths and cycles on conforming tetrahedral meshes

This paper addresses the existence and construction of Hamiltonian paths and Hamiltonian cycles on conforming tetrahedral meshes. The paths and cycles are constrained to pass from one tetrahedron to the next one through a vertex. For conforming tetrahedral meshes, under certain conditions which are normally satisfied in finite-element computations, we show that there exists a through-vertex Hamiltonian path between any two tetrahedra. The proof is constructive from which an efficient algorithm for computing Hamiltonian paths and cycles can be directly derived.     

Parallel construction of Hamiltonian paths for conforming tetrahedral meshes

In this paper, we address the construction of a Hamiltonian path for conforming tetrahedral meshes on distributed memory machines. The path is constrained to pass from one element to the next one through a vertex. For a conforming tetrahedral mesh whose dual graph is connected, if it can be split into many submeshes and the dual graphs of these submeshes are connected, then we can construct partial Hamiltonian paths for all submeshes independently and a Hamiltonian path for the mesh can be obtained by connecting these partial Hamiltonian paths.     

On an automatically parallel generation technique for tetrahedral meshes

A program for the efficient parallel generation of tetrahedral meshes in a wide class of three-dimensional domains having a generalized cylindrical shape is presented. The applied mesh generation strategy is based on the decomposition of some 2D-reference domain into simply connected subdomains. By means of the reference triangulations of these subdomains the tetrahedral layers are built up in parallel. Adaptive grid controlling as well as nodal renumbering algorithms are involved. In the paper several examples are included to demonstrate both the capabilities of the program and the adequate handling with the implemented method of parallelization.     

Direct volume rendering of unstructured tetrahedral meshes using CUDA and OpenMP

Direct volume visualization is an important method in many areas, including computational fluid dynamics and medicine. Achieving interactive rates for direct volume rendering of large unstructured volumetric grids is a challenging problem, but parallelizing direct volume rendering algorithms can help achieve this goal. Using Compute Unified Device Architecture (CUDA), we propose a GPU-based volume rendering algorithm that itself is based on a cell projection-based ray-casting algorithm designed for CPU implementations. We also propose a multicore parallelized version of the cell-projection algorithm using OpenMP. In both algorithms, we favor image quality over rendering speed. Our algorithm has a low memory footprint, allowing us to render large datasets. Our algorithm supports progressive rendering. We compared the GPU implementation with the serial and multicore implementations. We observed significant speed-ups that, together with progressive rendering, enables reaching interactive rates for large datasets.     

Discretizations for weighted condition number smoothing on general unstructured meshes

New method for weighted condition number smoothing of general unstructured computational meshes is presented. Its core, proper discretization of weighted smoothness functional, is detailed, options of particular implementation are discussed and demonstrated on general convex polygonal cells in two dimensions. Possible applications of this algorithm are suggested, namely solution-sensitive mesh adaptation (respecting the variation of some variable) and prevention of unwanted smoothing effects on polar meshes.     

Grid-characteristic method using high-order interpolation on tetrahedral hierarchical meshes with a multiple time step

The purpose of the present paper is to develop a grid-characteristic method for high-performance computer systems using unstructured tetrahedral hierarchical meshes, a multiple time step and the high-order interpolation for simulating complex spatial dynamic processes in heterogeneous environments. This method has the precise formulation of contact conditions and is suitable for the physically correct solution of seismology and seismic prospecting problems in complex heterogeneous environments. The use of the hierarchical meshes allows us to take into account a large number of nonhomogeneous inclusions (cracks, cavities, etc.). The use of this grid-characteristic method makes it possible to use a multiple time step and thereby increase productivity and significantly reduce the computation time. The methods developed for high-order interpolation on unstructured tetrahedral meshes can solve the problems of seismology and seismic prospecting with approximation in space of up to the fifth degree (inclusive).     

User controllable anisotropic shape distribution on 3D meshes

Computational Visual Media - This paper presents an automatic method for computing an anisotropic 2D shape distribution on an arbitrary 2-manifold mesh. Our method allows the user to specify the...     

Cell-centered quasi-one-dimensional reconstruction scheme on 3D hybrid meshes

This paper presents a cell-centered conservative scheme based on a quasi-one-dimensional (1D) reconstruction of variables for the solution of a system of hyperbolic equations on 3D unstructured meshes. Only the case of smooth solutions is considered. Test examples are used to demonstrate that the accuracy and computational costs of the studied scheme are about the same as of the vertexcentered EBR scheme and the preferability of the vertex-centered or cell-centered scheme is determined by the prevalent types of elements in the computational mesh.     

基于人物状态自动机的实时动态寻径算法优化

路径搜索是实现游戏中的角色逼真行走的关键技术之一.针对游戏动态路网中寻径极易陷入陷阱且寻径效率不高的问题,将人物状态自动机和加权的LRTA*算法相结合,提出了基于人物状态自动机的实时动态寻径算法.通过改变估价函数值更新规则与解时间和解质量相结合,加快算法收敛速度,并引入人工搜索标志,完成对LRTA*算法的优化.测试结果表明,该算法有效提高了路径搜索的速度,并使搜索得到的路径平滑自然.     

Combined compression and simplification of dynamic 3D meshes

We present a new approach to dynamic mesh compression, which combines compression with simplification to achieve improved compression results, a natural support for incremental transmission and level of detail. The algorithm allows fast progressive transmission of dynamic 3D content. Our scheme exploits both temporal and spatial coherency of the input data, and is especially efficient for the case of highly detailed dynamic meshes. The algorithm can be seen as an ultimate extension of the clustering and local coordinate frame (LCF)‐based approaches, where each vertex is expressed within its own specific coordinate system. The presented results show that we have achieved better compression efficiency compared to the state of the art methods. Copyright © 2008 John Wiley & Sons, Ltd.     

3维牙颌模型牙齿分割的路径规划方法

目的 从3维牙颌模型上分割出单颗牙齿是计算机辅助正畸系统的重要步骤。由于3维测量分辨率和网格重建精度的有限性,三角网格牙颌模型上牙龈和牙缝边界往往融合在一起,使得单颗牙齿的自动分割变得极为困难。传统方法容易导致分割线断裂、分支干扰等问题,且手工交互较多,为此提出一种新颖的基于路径规划技术的单颗牙齿自动分割方法。方法 为避免在探测边界时牙龈和牙缝相互干扰,采用牙龈路径和牙缝路径分开规划策略。首先基于离散曲率分析和一种双重路径规划法搜索牙龈分割路径,并基于搜索到的牙龈路径利用图像形态学和B样条拟合技术构建牙弓曲线;然后综合牙龈路径和牙弓曲线的形态特征探测牙龈路径上的牙缝凹点以划界每颗牙齿的牙龈边界轮廓,并通过匹配和搜索牙龈边界轮廓上颊舌侧凹点间的最优路径确定齿间牙缝边界路径;最后细化整个路径以获取每颗牙齿精确的封闭分割轮廓。结果 对不同畸形程度的患者牙颌模型进行分割实验,结果表明,本文方法对于严重畸形的牙齿能够产生正确的分割结果,而且简单快速,整个分割过程基本能够控制在20 s以内。和现有方法相比,本文方法具有较少的人工干预和参数调整,除了在个别牙齿边界较为模糊的位置需要手动调整外,大部分情况都是自动的。结论 提出的路径规划方法具有强大的抗干扰能力,能够有效克服牙缝牙沟等分支干扰以及分割线断裂等问题,最大程度地减少人工干预,适用于各类畸形牙患者模型的牙齿分割。     

Key-components: detection of salient regions on 3D meshes

In this paper, we present a method to detect stable components on 3D meshes. A component is a salient region on the mesh which contains discriminative local features. Our goal is to represent a 3D mesh with a set of regions, which we called key-components, that characterize the represented object and therefore, they could be used for effective matching and recognition. As key-components are features in coarse scales, they are less sensitive to mesh deformations such as noise. In addition, the number of key-components is low compared to other local representations such as keypoints, allowing us to use them in efficient subsequent tasks. A desirable characteristic of a decomposition is that the components should be repeatable regardless shape transformations. We show in the experiments that the key-components are repeatable and robust under several transformations using the SHREC’2010 feature detection benchmark. In addition, we discover the connection between the theory of saliency of visual parts from the cognitive science and the results obtained with our technique.     

基于样本选取和加权KPCA-L1的异常检测*

为了提高基于一范数的核主成分分析算法（KPCA-L1）处理异常检测问题的速度,提出了基于样本选取和加权KPCA-L1的异常检测方法。所提方法首先从训练集中选取具有代表性的特征子集,然后为所得特征子集中的样本赋予权重,用带有权重的特征子集训练模型,构造加权KPCA-L1。与KPCA-L1相比,所提方法能够有效地减小训练集的规模,同时改善了KPCA-L1算法的更新方法。在人工数据集和标准数据集上的实验结果表明,在保证异常检测准确率的前提下,所提方法比KPCA-L1具有更快的建模速度。     

Using interpolation to improve path planning: The Field D* algorithm

We present an interpolation‐based planning and replanning algorithm for generating low‐cost paths through uniform and nonuniform resolution grids. Most grid‐based path planners use discrete state transitions that artificially constrain an agent's motion to a small set of possible headings (e.g., 0, π/4, π/2, etc.). As a result, even “optimal” grid‐based planners produce unnatural, suboptimal paths. Our approach uses linear interpolation during planning to calculate accurate path cost estimates for arbitrary positions within each grid cell and produce paths with a range of continuous headings. Consequently, it is particularly well suited to planning low‐cost trajectories for mobile robots. In this paper, we introduce a version of the algorithm for uniform resolution grids and a version for nonuniform resolution grids. Together, these approaches address two of the most significant shortcomings of grid‐based path planning: the quality of the paths produced and the memory and computational requirements of planning over grids. We demonstrate our approaches on a number of example planning problems, compare them to related algorithms, and present several implementations on real robotic systems.