二维Delaunay三角网局部更新:点插入与点删除

二维Delaunay三角网的局部更新在地学分析、道路CAD、城市规划等领域有着广泛的用途,点插入和点删除则是其中最重要、最基本的操作。该文针对原有逐点插入法和凸耳权值点删除算法存在的不足,利用动态包围三角形和特征三角形分别对其进行改进,在设计的具有拓扑关系Delaunay的三角网数据结构基础上,实现Delaunay三角网的快速局部更新,且使之满足Delaunay特性。最后通过模拟实验验证了算法的正确性和高效性。     

二维Delaunay三角网的任意点删除算法研究

针对目前基于影响域多边形剖分的点删除算法缺陷,提出一种二维Delaunay三角网点删除算法。首先利用具有拓扑关系的三角网搜索影响多边形,并以三角形矢量面积为工具三角剖分影响域多边形,最后通过镶嵌优化后的剖分三角网完成点的删除,且满足Delaunay法则。通过测试证明了算法的可靠性和高效性。     

基于线性和岛屿约束的Delaunay三角网构建算法研究

针对基于线性和岛屿约束的Delaunay三角网构建算法的不足,从减少算法计算机实现步骤出发,研究改进了线段相交判断、首三角形确定等影响域多边形搜索相关算法;在分析当前存在的多边形三角剖分算法基础上,给出了存在重复点(悬边)的多边形三角剖分算法;在影响域多边形搜索阶段充分利用多边形间的拓扑关系信息,消除了岛屿约束内部三角形删除时需遍历三角形数据的不足.算法涵盖线性和岛屿约束的构建,综合性强,效率高且易于实现.     

Delaunay三角网约束的Harris-SURF图像匹配算法

Harris算法提取的角点定位精度高,但不具尺度不变性,SURF算法虽具有尺度不变性和旋转不变性,但提取的特征点并非视觉角点。针对此问题,该文提出一种Delaunay三角网约束下的Harris-SURF图像匹配方法。首先,采取阈值评估策略对图像进行SURF粗匹配,利用RANSAC算法进行粗差剔除,得到的匹配点用于构建Delaunay三角网;然后以相似三角形作为约束,将其作为Harris特征点精匹配的限制区域,提高Harris点匹配的可靠性。实验表明,该算法具有匹配准确率高、鲁棒性较好等特点,对无人机影像的匹配效果明显优于其他算法。     

基于四叉树索引构建TIN的高效合成算法

不规则三角网(TIN)可以逼真的模拟地形表面,因此被广泛应用于地学领域。Delaunay三角剖分算法是构建TIN网的最优算法,该文对传统Delaunay三角网构建算法进行分析,提出了一种针对大规模离散数据点生成TIN的高效合成算法。该算法首先根据离散点的分布位置和密度对其进行四叉树区域划分;然后以每个叶子节点的边界四边形为凸包,采用逐点插入法构建三角网;最后采用顶点合并法自底向上合并具有相同父节点的4个子节点,生成Delaunay三角网。实验结果表明,该算法时间复杂度较低,有效提高了TIN网的构建效率。     

约束Delaunay三角网点删除的一体化凸耳消元法(IEE)

对Delaunay三角网(CD—TIN)点删除算法——凸耳消元法(EE)进行剖析,提出约束Delaunay三角网的点删除算法——体化凸耳消元法(IEE)。该算法将CD-TIN的点删除转化为点的影响域重构,并保证重构后的CD—TIN满足CD—TIN的可视性与空圆法则,确保了CD—TIN的拓扑完备性,实现了CD—TIN中约束点与非约束点删除的一体化操作和局部更新,并得到实验验证。     

基于三角形驱动的机载LiDAR数据栅格化算法

针对基于TIN的机载LiDAR点云数据插值为GRID过程中,大量TIN数据I/O操作导致的栅格化效率下降问题,提出了基于三角形驱动的点云栅格化流式算法:以基于直线正负区判别原理的TIN向GRID转换新算法为基础,通过遍历三角形模拟流计算实现三角形生成、三角形插值为GRID以及内存释放,有效避免了TIN数据的I/O操作,并可以提高内存利用率。试验表明:流式算法显著提高了点云栅格化效率,为海量点云的栅格化及并行计算提供了一种算法支撑。     

自适应的IDW插值方法及其在气温场中的应用

反距离权重(Inverse Distance Weighting,IDW)插值通常采用距离搜索策略选择插值参考点,当采样点集分布不均匀时,距离搜索策略使得参考点聚集一侧影响插值精度。自然邻近关系具有良好的自适应分布特性,可有效地解决参考点分布不均匀问题。结合自然邻近关系,提出自适应的反距离权重(Adaptive-IDW,AIDW)插值方法。首先对采样数据构建初始Delaunay三角网,然后采用逐点插入法,将待插值点插入初始Delaunay三角网中,局部调整得到新的Delaunay三角网,以待插值点的一阶邻近点作为IDW插值的参考点,使参考点自适应均匀地分布在待插值点周围,再进行IDW插值计算。利用AIDW插值方法对Franke函数、全国气温观测数据进行插值实验,结果表明此方法具有较高的精度,且减少了“牛眼”现象。     

等高线约束的Delaunay三角网在土石方量计算中的应用

土石方量计算是工程建设的重要步骤,其计算精度是提高工程质量的首要问题。针对利用无约束不规则三角网计算土石方量时存在的计算精度问题,该文利用三维激光点云数据,根据约束Delaunay三角网的构建原理,探讨了基于等高线约束的Delaunay三角网方法在土石方量计算中的应用。首先,以土石方的等高线作为约束线,利用迭代算法对无约束不规则三角网进行剖分,构建等高线约束Delaunay三角网,并进行土石方量计算。然后,将计算结果与无约束不规则三角网、方格网法计算结果进行对比与误差分析,验证了该方法的计算精度,为基于三维点云数据的土石方量精确计算提供了参考。     

基于GIS的高质量约束Delaunay三角网格剖分

在分析现有非结构化网格剖分算法的基础上,提出了一种GIS支持下的改进分治算法实现约束Delaunay三角网格剖分.该方法利用了GIS的空间拓扑关系对算法输入数据进行预处理,基于三角形的统一数据结构实现了网格细化,对输出剖分网格进行准确的拓扑和约束条件的检查,并基于推进阵面算法思想,结合空间邻近拓扑关系实现了三角剖分节点和网格的重新编号,方便了实际问题中开边界条件的赋值,提高了计算效率.实例应用表明,该方法大大简化了数值模型非结构化网格剖分的前处理过程,集成了几种综合算法的优点,在保证原分治算法时间复杂度的基础上,提高了约束条件下Delaunay三角网格生成的质量.     

面向离散点的空间权重矩阵生成算法与实证研究

采用阈值法和k-近邻法度量空间上离散点间的空间邻接关系,针对不同的距离计算方式(欧式距离和曼哈顿距离)设计了面向离散点的空间权重矩阵生成算法,使用C#语言在计算机上实现。用该算法对收集的8 367个常州市地价样点构建了不同土地用途地价样点的空间权重矩阵,并计算出分用途的常州市城市地价空间自相关指数。     

动态广义表空间索引方法

提出了一种新的动态空间索引结构X-Lists,设计实现了X-Lists的动态插入、动态删除、查找等算法,并进行了算法实验。X-Lists是一种支持高维点查询和区域查询的广义表,实验表明,X-Lists在索引构建与区域查找方面性能明显优于现有R-Tree及其改进索引结构。     

An efficient incremental algorithm for generating the characteristic shape of a dynamic set of points in the plane

Several algorithms have been proposed to generate a polygonal ‘footprint’ to characterize the shape of a set of points in the plane. One widely used type of footprint is the χ-shape. Based on the Delaunay triangulation (DT), χ-shapes guaranteed to be simple (Jordan) polygons. This paper presents for the first time an incremental χ-shape algorithm, capable of processing point data streams. Our incremental χ-shape algorithm allows both insertion and deletion operations, and can handle streaming individual points and multiple point sets. The experimental results demonstrated that the incremental algorithm is significantly more efficient than the existing, batch χ-shape algorithm for processing a wide variety of point data streams.     

An efficient method for single-facility location and path-connecting problems in a cell map

This article presents an efficient method for simultaneously finding both the Weber cell and optimal connective paths in a grid. As numerous barriers of arbitrary shape and weighted regions are distributed in the cell map of this research, the problem scenario is similar to working out a real-life facility location selection and path-routing problems in a geographical map. In this study, the Weber problem of finding a single-facility location from an accumulation cost table is generated by a grid wave propagation method (higher-geometry maze router). After finding the Weber point (cell), optimal connective paths with minimum total weighted cost are backtracked between the Weber location cell and the demand cells. This new computation algorithm with linear time and space complexity can be integrated as a spatial analytical function within GIS.     

3D tree modeling from incomplete point clouds via optimization and L1-MST

Reconstruction of 3D trees from incomplete point clouds is a challenging issue due to their large variety and natural geometric complexity. In this paper, we develop a novel method to effectively model trees from a single laser scan. First, coarse tree skeletons are extracted by utilizing the L₁-median skeleton to compute the dominant direction of each point and the local point density of the point cloud. Then we propose a data completion scheme that guides the compensation for missing data. It is an iterative optimization process based on the dominant direction of each point and local point density. Finally, we present a L₁-minimum spanning tree (MST) algorithm to refine tree skeletons from the optimized point cloud, which integrates the advantages of both L₁-median skeleton and MST algorithms. The proposed method has been validated on various point clouds captured from single laser scans. The experiment results demonstrate the effectiveness and robustness of our method for coping with complex shapes of branching structures and occlusions.     

大规模地形实时绘制算法

该文提出一种适合大规模地形实时绘制的简单高效的LOD简化算法。该算法使用一种紧凑有效的规则网格表示方法,优化网格节点的数目,减少可视化过程中的计算量,降低额外内存开销。探讨该算法相关的数据组织、视域裁剪、LOD层次选择、裂缝消除、三角形化等关键问题。实验结果表明,该算法实现简单,内存开销较少,CPU耗费小,对图形卡要求低,能够在普通机器上实现大规模地形的实时漫游。     

Anchor uncertainty and space-time prisms on road networks

Space-time prisms capture all possible locations of a moving person or object between two known locations and times given the maximum travel velocities in the environment. These known locations or ‘anchor points’ can represent observed locations or mandatory locations because of scheduling constraints. The classic space-time prism as well as more recent analytical and computational versions in planar space and networks assume that these anchor points are perfectly known or fixed. In reality, observations of anchor points can have error, or the scheduling constraints may have some degree of pliability. This article generalizes the concept of anchor points to anchor regions: these are bounded, possibly disconnected, subsets of space-time containing all possible locations for the anchor points, with each location labelled with an anchor probability. We develop two algorithms for calculating network-based space-time prisms based on these probabilistic anchor regions. The first algorithm calculates the envelope of all space-time prisms having an anchor point within a particular anchor region. The second algorithm calculates, for any space-time point, the probability that a space-time prism with given anchor regions contains that particular point. Both algorithms are implemented in Mathematica to visualize travel possibilities in case the anchor points of a space-time prism are uncertain. We also discuss the complexity of the procedures, their use in analysing uncertainty or flexibility in network-based prisms and future research directions.     

Map-matching algorithm for large-scale low-frequency floating car data

Large-scale global positioning system (GPS) positioning information of floating cars has been recognised as a major data source for many transportation applications. Mapping large-scale low-frequency floating car data (FCD) onto the road network is very challenging for traditional map-matching (MM) algorithms developed for in-vehicle navigation. In this paper, a multi-criteria dynamic programming map-matching (MDP-MM) algorithm is proposed for online matching FCD. In the proposed MDP-MM algorithm, the MDP technique is used to minimise the number of candidate routes maintained at each GPS point, while guaranteeing to determine the best matching route. In addition, several useful techniques are developed to improve running time of the shortest path calculation in the MM process. Case studies based on real FCD demonstrate the accuracy and computational performance of the MDP-MM algorithm. Results indicated that the MDP-MM algorithm is competitive with existing algorithms in both accuracy and computational performance.