一种基于变量可达向量的链表抽象方法

提出了一种链表抽象表示方法.该方法隐式存储链表结点之间的边信息,并采用了一种紧致的链表状态表示,存储开销较低,且维护了链表长度信息,精确度较高.具体而言,根据变量对链表结点的可达性质定义了变量可达向量,采用带计数的变量可达向量集描述链表的形态及数量性质,并定义了基本链表操作的抽象语义.通过简单扩展,该方法可以建模包括环形链表在内的所有单向链表.最后,为了验证该链表抽象方法的正确性,在符号执行框架中进行实验,并对常见链表操作程序的运行时错误、长度相关性质等关键性质进行了分析与验证.     

一种基于八叉树与流水线技术的快速碰撞检测算法

针对存在大量运动物体的虚拟环境,提出一种基于空间八叉树剖分与流水线技术的并行碰撞检测算法.通过八叉树剖分,把虚拟空间剖分成一系列的子空间,然后只对同一空间中的结点进行碰撞检测.对空间内的每个物体构建包围盒树,同一空间中的任意两棵包围盒树遍历构成任务树,把任务树中的任务分配给不同的进程进行碰撞检测,并采用流水线与多线程技...     

基于B+树存储的AABB包围盒碰撞检测算法

对于碰撞检测算法,使用传统的AABB包围盒来构建包围盒层次树时,其包围盒层次树的层数、叶子结点的个数和各结点的存储字节数是影响碰撞检测效率的主要因素.为了减少结点存储容量对碰撞检测效率的影响,提高碰撞检测的效率,文中采取B+树的存储结构来存储包围盒等信息.在包围盒相交测试之前,使得各结点存储索引有序,不需要再对各结点进行额外的排序,减少了内存开销,并且避免了不必要的包围盒测试.此外B+树的非叶子结点不存储具体的数据信息,从而减少了整棵树的存储空间.实验表明,在检测环境和检测对象相同的条件下,使用B+树存储的AABB包围盒碰撞检测算法的检测时间明显比传统的AABB算法短.     

基于层次包围盒的碰撞检测算法的存储优化

介绍了基于层次包围盒的碰撞检测算法的存储优化方法。该方法从存储空间的角度来改进基于AABB树的碰撞检测算法。根据AABB树的构造过程,减少内部节点的AABB包围盒的存储字节数;基于快速三角形相交测试算法,从叶节点结构里去掉包围盒信息,将叶节点从存储结构中删除。实验表明,利用AABB包围盒和叶节点的存储优化,既减少了算法的存储空间又加快了算法的执行时间。     

LinkNet:一种用于大规模P2P系统查找的新方法

提出了一种新的可扩展分布式数据结构LinkNet来支持大规模P2P系统中的数据查找.在LinkNet中,所有的元素存储在一个有序的双向链表中,该链表中的每个结点都可以存储多个元素.LinkNet使用虚拟链接来减少存储开销和加速查找过程.在一个包含N个结点M个元素的网络中,LinkNet占用的存储空间期望值为O（M）,并且当M足够大时,查找操作期望只需要传递O（logN）条消息.     

基于XML和关系数据库的树形结构的研究

本文介绍了一种树型结构的存储、显示和维护方法。以二叉链表的数据结构将树的信息存储在数据库中，服务器端将数据库中树的信息转化成XML，客户端将其加载到浏览器的（DOM）实例中，并采用深度优先搜索算法对该实例中的结点进行递归遍历，生成浏览器端树的HTML代码，它是一个与上述XML文档逻辑相同的树型结构。同时在各结点上设置JS事件，可以对该树进行维护，生成针对结点维护的XML，服务器解析该XML并生成一系列SQL提交到数据库中。     

USSCD：一个基于均匀空间分割的快速碰撞检测算法

对于存在大量运动物体的虚拟环境，碰撞检测往往成为影响系统计算效率的瓶颈，为提高多体碰撞检测的效率，提出了一个基于均匀空间分割的快速多体碰撞检测算法——USSCD，该算法首先将物体空间均匀分割成一系列单元格，然后在每个单元格，通过基于AVL排序的扫描排除法进行碰撞检测，同时依据物体的分布密度，提出了一个计算单元格尺寸的优化方法，通过一系列实验，测试了USSCD算法的性能，并与I-COLLIDE算法进行比较，实验结果表明，在均匀分布条件下，当物体数量较大时，USSCD的效率高于I-COLLIDE算法，而且，USSCD算法的效率基本不受物体运动相关性的影响。     

大型有向图的三叉链表式存储结构

为了对大型有向图进行存储,提出了一种三叉链表式的存储结构。它由索引链表、结点链表、连结链表按照一定结构组成。可以较好地满足某些大型有向图的存储要求,具有节约存储空间、算法适用面宽、可维护性好等特点。     

基于时空相关性的快速碰撞检测算法

针对如何提高碰撞检测算法实时性的问题,提出一种空间分解与层次包围盒相结合的碰撞检测算法,并利用物体运动的时空相关性来加速物体之间的碰撞检测速度。首先用空间分割的方法确定相邻物体,然后用基于时空相关性的层次包围盒方法检测物体之间的碰撞情况,在包围盒碰撞检测时采用加入预判的OBB相交测试方法,减少了包围盒的相交测试计算。实验结果表明,该算法能够实现多个物体同时发生碰撞的检测,并且提高碰撞检测的实时性。     

几何数据压缩的一种新算法

本文提出一种几何数据压缩的新算法,其基本思想是在已知物体网格边界的条件下,首先寻找边界的凹点,然后建立网格结点的特殊树结构,即横切面树,并将横切面树中相邻节点内网格结点之间的关系表示为链表（三角形条带）,按契约数结构及链表（三角形条带）编码、存储帮传输网格结点的连接关系,这种算法不同于Gabriel Taubin算法,它具有对顶点坐标、属性坐标及三角形连接关系压缩无损等许多优点。     

Octree generation from object silhouettes in perspective views

Octrees are useful for object representation when fast access to coarse spatial occupancy information is necessary. This paper presents an efficient algorithm for generating octrees from multiple perspective views of an object. The algorithm first obtains a polygonal approximation of the object silhouette. This polygon is then decomposed into convex components. For each convex component, a pyramid is formed treating the view point as its apex and the convex components as a cross section. The octree representation of each of these pyramids is obtained by performing intersection detection of the object with the cubes corresponding to octree nodes. The intersection detection step is made efficient by decomposing it into a coarse-to-fine sequence of intersection tests. The octree for one silhouette is obtained by taking the union of octrees obtained for each component. An intersection of octrees corresponding to different viewing directions gives the final octree of the object. An implementation of the algorithm is given. The accuracy of the octree representation of the objects is evaluated. The ratio of the actual volume of the object to the volume of the object reconstructed from the octree representation is used as a performance index of the algorithm.     

基于面向对象八叉树的飞机虚拟维修场景渲染

为了加速大规模虚拟场景的渲染速度,采用基于面向对象八叉树的方法对场景进行渲染。该方法将面向对象技术与传统八叉树技术相结合,采用面向对象八叉树剖分虚拟场景,对场景进行管理;将物体结构树的最小零部件作为最小存储单元,采用叶节点保存对象信息,减小树的存储量和处理时间,降低算法的计算负担;在面向对象八叉树的基础上,采用模型遮挡裁剪算法对位于视域范围内的模型进行遮挡裁剪,减小实际渲染的物体数量,提高渲染速率。通过对飞机虚拟维修场景进行渲染实验,证明了该方法的有效性。     

复杂场景中基于拓扑空间网格的碰撞检测算法

为了提高复杂场景的碰撞检测效率,提出一种基于拓扑空间网格的碰撞检测算法. 由于场景中存在众多形状复杂、尺寸不一且运动状态不同的物体,首先采取场景预处理对空间进行均匀八叉树网格划分,建立物体方向包围盒层次树与空间网格拓扑结构,利用静态大尺寸物体分割策略提升定位精确性,然后在实时检测中利用拓扑空间网格及投影相交测试排除大量不相交物体对,利用层次包围盒算法对潜在碰撞对进行精确检测并计算出碰撞点. 实验结果表明,本算法有效地提高了实时检测的效率,适用于复杂虚拟场景中的碰撞检测.     

复杂网络半监督的社区发现算法研究

随着大数据时代的到来,复杂网络的社区发现已成为一个重要研究方向。层次聚类算法作为社区发现的经典算法受到了广泛应用,然而该算法具有较高的时间复杂度和较低的运行效率。为提高社区发现算法的运行效率,提出了一种基于节点相似度的半监督社区发现新算法--SSGN算法。充分利用先验知识must-link、cannot-link约束集合,将先验信息通过衍生规则进行扩展,并对扩展的信息通过基于距离度量的方式加以验证。采用人工网络和真实网络进行验证,UCI 数据集和大型真实数据集上的实验结果表明, 基于节点相似度的半监督社区发现算法较其他半监督聚类算法更准确,也更高效。     

Visualizing nonmanifold and singular implicit surfaces with point clouds

We use octree spatial subdivision to generate point clouds on complex nonmanifold implicit surfaces in order to visualize them. The new spatial subdivision scheme only uses point sampling and an interval exclusion test. The algorithm includes a test for pruning the resulting plotting nodes so that only points in the closest nodes to the surface are used in rendering. This algorithm results in improved image quality compared to the naive use of intervals or affine arithmetic when rendering implicit surfaces, particularly in regions of high curvature. We discuss and compare CPU and GPU versions of the algorithm. We can now render nonmanifold features such as rays, ray-like tubes, cusps, ridges, thin sections that are at arbitrary angles to the octree node edges, and singular points located within plot nodes, all without artifacts. Our previous algorithm could not render these without severe aliasing. The algorithm can render the self-intersection curves of implicit surfaces by exploiting the fact that surfaces are singular where they self-intersect. It can also render the intersection curves of two implicit surfaces. We present new image space and object space algorithms for rendering these intersection curves as contours on one of the surfaces. These algorithms are better at rendering high curvature contours than our previous algorithms. To demonstrate the robustness of the node pruning algorithm we render a number of complex implicit surfaces such as high order polynomial surfaces and Gaussian curvature surfaces. We also compare the algorithm with ray casting interms of speed and image quality. For the surfaces presented here, the point clouds can be computed in seconds to minutes on atypical Intel based PC. Once this is done, the surfaces can be rendered at much higher frame rates to allow some degree of interactive visualization.     

An algorithm for converting the boundary representation of a CAD model to its octree representation

Present CAD systems store the solid model of an object using a convenient representation. Boundary models and CSG (Constructive Solid Geometry) models are the most frequently used representations. Based on recent research findings, octree representation of an object presents a promising approach in solving problems in the areas of Computer Graphics, Manufacturing and Robotics. The most notable use of octree representations is in CAD-based robotic path planning problems. Octree models have also been used in fast rendering of 3-D solid models using ray tracing methods. This paper presents an algorithm for converting the boundary representation of polyhedral models to its octree representation. Such an algorithm would provide the link between an object generated using a solid modelling system and the application involving an octree representation of an object. The algorithm is demonstrated by converting a polyhedral boundary model of a sample object to its octree representation.     

无人车驾驶场景下的多目标车辆与行人跟踪算法

考虑到现有的基于检测的多目标跟踪算法多会出现因目标漏检或数据关联算法冗余而造成的目标ID频繁切换、跟踪轨迹断开等问题,提出了无人车驾驶场景下的多目标车辆与行人跟踪算法.首先,选取CenterNet网络作为目标检测器,并用嵌入了1×1卷积和SE-Net的Res2Net来替代网络原有的残差单元,以提升网络对空间信息和通道信息的提取能力,提高目标检测器性能.接着,用孪生网络来提取目标所在区域的特征,进行关联概率度量,再用匈牙利算法对相邻帧目标进行关联.最后,用区域推荐网络设计的辅助跟踪器对漏检或消失又出现的目标进行持续跟踪,并将可靠的跟踪结果合并到轨迹中.实验结果表明,与已有的方法对比,所提方法在KITTI跟踪基准数据集上对于车辆与行人的跟踪具有竞争力.     

基于随机森林的目标检测与定位

为解决复杂图像中的目标检测与定位问题,提出一种基于随机森林的目标检测与定位算法。采用SIFT局部特征构造随机森林分类器,以一个决策树中的全部叶子节点构成一个树型结构的判别式码本模型,从而获得更可靠的概率Hough投票,加快目标检测速度。实验结果证明,该算法效率较高,可用于复杂场景下的目标检测与定位。     

Symmetry identification of a 3-D object represented by octree

An algorithm for identifying symmetry of a 3-D object given by its octree is presented, and the symmetry degree (a measure of object symmetry) is proposed. The algorithm is based on traversals of the octree obtained by the principal axis transform of an input octree. An object can be in an arbitrary position and with arbitrary orientation within the octree space, and a wide range of symmetries represented by groups of proper and improper rotations can be identified. It is shown that the octree data structure supports these operations well, especially for objects whose symmetry types are simpler or equal in complexity with a fourfold rotational symmetry. The operation of the algorithm is illustrated using some synthetic test objects. The results, which are composed of identified symmetry types and the corresponding symmetry degrees, were satisfactory     

基于八叉树空间分割的三维点云模型密写

针对三维点云模型的信息隐藏,提出一种基于八叉树空间分割的空域密写算法。对经过主成分分析后的三维点云模型建立包围盒,利用八叉树空间分割得到小体元并记录分割过程,通过顶点位移将信息嵌入到小体元内的不同空间位置。实验结果表明,该算法在提取信息时不需要原始模型数据,具有嵌入量高、失真度低的特点,能够抵抗旋转、平移、均匀缩放和顶点重排序攻击,适合于任意网格的三维模型信息隐藏。