基于拓扑不变性的GSRBF隐式曲面重建

为提高大规模点云曲面重建的精度和效率,提出一种基于拓扑不变性的全局支撑的径向基函数(GSRBF)隐式曲面重建算法。结合Hausdorff算法,根据点云的主曲率和高斯曲率引入一个临界值,防止提取特征点时产生较大误差,构造特征点点云拓扑同胚的拓扑结构;引入八叉树网格划分法进行点云拓扑关系的构造,通过构造与模型控制网格拓扑同胚的拓扑结构来重建曲面的拓扑;构造基函数确定特征点的影响范围,将其归一化得到曲面拓扑上的单位分解,复合单位分解与特征点得到隐式曲面。实验结果表明,该算法适用于任意拓扑的曲面重建,具有较高的精度和效率。     

一种网格融合算法

快速建模是三维游戏动画领域的重要技术,从已有模型经过修改、编辑、融合构建出新的模型是一种高效的建模方法.本文提出了一种网格模型融合算法,该算法首先将需要的部分网格从源模型上交互剪切下来,并将其配准对齐;然后将两网格模型转化成点模型表示,并将点模型转化成RBF隐函数表示;再对两隐函数进行布尔运算;最后将布尔运算生的隐函数曲面在两网格接合区域进行三角形化,得到最终的网格模型.算法定义了隐函数曲面的影响区域,有效控制融合过渡.采用边界扩展的三角形化方法,保留了融合区域以外源模型的特征.实验结果表明,本文算法具有很好的网格融合结果,可用于游戏动画中快速造型.     

点云数据在深度学习中表示方法的研究

为了实现在深度学习中能够端到端表示点云模型,提出基于八叉树和K-D树（OctKD）的点云数据表示方法。该方法将无组织的点云转换为体素空间,在体素空间对三维模型进行八叉树剖分,改进了八叉树编码方式;构建节点间的邻接关系,在GPU端并行构建八叉树;为了克服八叉树编码检索效率低的问题,采用三维K-D树索引单个三维空间点。实验结果表明该方法能够真实反映模型本身的细节特征,提高了点云模型的构造时间和检索效率。这种新的数据结构实现将点云转换为卷积神经网络可以接收的数据形式。     

一般点模型的交互式布尔运算

提出了一个适用于一般点模型的交互式布尔运算算法,此算法由4个步骤组成．首先将点模型表示为自适应的三色八叉树,然后利用自适应八叉树结构加速内外测试．对于局部采样密度不一致的相交区域或曲率太大容易导致较大求交误差的地方,实行了自适应细分加密采样;重采样相交的部分以获得更精确的求交结果．与已有的点模型布尔运算方法相比,该算法适用于一般的实测点云数据,包括少量噪声的点模型、非均匀采样以及不同分辨率点模型之间的交互式布尔运算。     

基于隐式T样条的曲面重构算法

提出隐式T样条曲面，将T网格从二维推广到三维情形，同时利用八叉树及其细分过程，从无结构散乱点数据集构造T网格，利用曲面拟合模型将曲面重构问题转化为最优化问题；然后基于隐式T样条曲面将最优化问题通过矩阵形式表述，依据最优化原理将该问题转化成线性方程组，通过求解线性方程组解决曲面重构问题；最后结合计算实例进行讨论．该方法能较好地解决曲面重构问题，与传统张量B样条函数相比，能效地减少未知控制系数与计算量．     

基于径向基函数网络的隐式曲线

将径向基函数网络与隐式曲线构造原理相结合,提出了构造隐式曲线的新方法,即首先由约束点构造神经网络的输入与输出,把描述物体边界曲线的隐式函数转化为显式函数,然后用径向基函数网络对此显式函数进行逼近,最后由神经网络的仿真曲面得到物体边界的拟合曲线．实验表明,基于径向基函数网络的隐式曲线具有很强的物体边界描述能力和缺损修复能力．     

MPU算法在汽车车身造型设计中的应用

介绍了多层面单位分割隐函数曲面(MPU)算法.该算法建立在局部形状函数、单位分割和八叉树细分的基础上,可由点云数据快速、准确、自适应地进行曲面反求.应用该算法,对车身外覆盖件和内部结构件进行了曲面反求,结果表明,该算法对汽车车身开发具有重要的应用价值.     

基于八叉树空间分割的NURBS曲面重构方法

对三维模型和点云曲面重构方法进行深入研究,根据应用特点提出八叉树空间分割和N U RBS曲面重构方法。利用八叉树的快速收敛特性对三维实体的点云数据进行分割、精简,采用N U RBS方法对局部网格曲面进行重构;采用八叉树和四叉树相混合的数据结构,渐进地进行网格曲面的重构。存储结构采用扩展式八叉树结构,编码采用8进制前缀编码方法。利用O penG L设计一个实验模型系统验证了该算法的可行性和有效性。     

一种新的基于发散度函数的地形模型简化方法

提出了一种新的地形模型简化方法,该方法是在隐式四叉树层次结构基础上,结合离散粒子群思想建立地形的简化模型.文中重新定义粒子为具有层次信息的特征点的集合,从而每个粒子与简化模型的一个候选解相对应.为了实现多个粒子的空间压缩和快速检索,给出了隐式四叉树层次结构的快速索引方法.此外提出了基于法向矢量夹角的发散度函数的误差计算方法,重新定义了既满足地形模型误差要求同时兼顾模型简化比例的粒子评价函数,使地形简化模型在保持细节特征和轮廓特征的同时获得了更优的简化比率和模型精度.最后采用最优粒子作为启发信息引导简化过程,因此多个粒子迅速收敛于最优简化模型,从而模型的简化效率大大提高.文中方法均在多个基准数据上进行实验研究,结果表明与经典层次简化方法相比,算法效率和模型精度均显著提高.     

基于BP神经网络的隐式曲线构造方法

隐式曲线与曲面是当前计算机图形学研究的热点之一。通过把BP神经网络与隐式曲线构造原理相结合，提出了一种构造隐式曲线的新方法，即首先由约束点构造神经网络的输入与输出，把描述物体边界曲线的隐式函数转化为显式函数；然后用BP神经网络对此显式函数进行逼近；最后由仿真曲面得到物体边界的拟合曲线。该新方法不同于传统的对显式函数的逼近方法，因为传统方法无法描述封闭的曲线；也不同于基于优化的拟合隐式曲线方法，因为它无须考虑函数的形式或多项式的次数。实验表明，该新方法有很强的物体边界描述能力和缺损修复能力，因而在物体边界重建、缺损图像复原等领域有一定的应用前景。     

3-D object decomposition with extended octree model and its application in geometric simulation of NC machining

The paper discusses the development of a prototype solid modeling system based on the extended octree modeling approach and its applications in 3-D NC machining simulation and automatic verification. Along with a simple hierarchical data structure, the extended octree model uses the face boundary information (i) to represent complex objects, (ii) to improve object representational accuracy, and (iii) to accelerate the model updating procedures in a graphic simulation process. The improved representational accuracy makes it possible to carry out automatic NC program verification by generating the machined model of the part through the simulation and comparing it with the designed model of the part. The paper also addresses the issues of model conversions from CSG and B-Rep schemes to the corresponding extended octree models and the issues of carrying out Boolean operations on those extended octree models. A prototype system has been implemented and is integrated with AutoCAD AME solid modeler for object modeling and for NC simulation purpose.     

大规模网格模型间的快速视觉布尔运算

为了解决产品设计阶段中大规模网格模型间的布尔运算无法实现立等可得的速度瓶颈,提出了一种新算法。该算法利用离散化采样获得射线段点云模型,将三角面片间的3D布尔运算转换为射线段间的1D布尔运算,对相交处的交点进行高精度的求解和插值处理,使得布尔运算速度大为提高,从而大大提升复杂拓扑结构的产品设计效率。通过该算法所获得射线段点云模型可获得等同于基于三角网格的渲染效果,该方法可进行工程应用。     

基于隐函数插值的连续多分辨率模型

提出了一种基于变分隐函数插值的连续多分辨率模型生成算法,通过递归地删除网格模型中的边得到连续的简化模型.算法采用变分隐函数插值的方法对网格模型分区域插值,生成原始模型的区域插值隐函数曲面,并以对应隐函数曲面上的采样点作为边折叠的目标点.算法建立了可调加权控制函数来控制边的简化顺序.在模型简化过程中,可通过交互调节控制函数的权值执行不同的简化原则,使得重要度低的边优先删除.此外,通过建立独立集,避免了模型的局部过度简化.实验结果表明,此算法能实现较理想的简化效果.     

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.     

A local adaptation-based generation method of medial axis for efficient engineering analysis

Currently engineering analysis is regarded as an integrated part of design process and medial axis (MA) is often utilized. However, the generation of MA of complicated models is computation intensive since it is always generated from scratch even if a tiny modification is imposed. A novel local adaptation-based approach to generating the MA for efficient engineering analysis is proposed in this study. With this method, the MA of a resultant model constructed from two other models via a Boolean operation or parameter modification is generated by adapting the MAs of the operand models in a certain way, instead of regenerating the MA from scratch. First, several new properties of the MA which are the fundamental basis of the proposed method are investigated. Then, the boundaries that will vanish from or be added into the resultant model during the Boolean operation or parameter modification are found, and the region in which the MA segments (MASs) need to be regenerated is determined. Finally, the new MASs are generated for the region using an improved tracing method. The final MA of the resultant model is thus constructed by combining the newly generated MASs with the reserved MASs of the operated model(s). Some examples are given to illustrate the high computational efficiency of the proposed method for engineering analysis.     

Novel Techniques for Robust Voxelization and Visualization of Implicit Surfaces

Voxelization is the transformation of geometric surfaces into voxels. Up to date this process has been done essentially using incremental algorithms. Incremental algorithms have the reputation of being efficient but they lack an important property: robustness. The voxelized representation should envelop its continuous model. However, without robust methods this cannot be guaranteed. This article describes novel techniques of robust voxelization and visualization of implicit surfaces. First of all our recursive subdivision voxelization algorithm is reviewed. This algorithm was initially inspired by Duff's image space subdivision method. Then, we explain the algorithm to voxelize implicit surfaces defined in spherical or cylindrical coordinates. Next, we show a new technique to produce infinite replications of implicit objects and their voxelization method. Afterward, we comment on the parallelization of our voxelization procedure. Finally we present our voxel visualization algorithm based on point display. Our voxelization algorithms can be used with any data structure, thanks to the fact that a voxel is only stored once the last subdivision level is reached. We emphasize the use of the octree, though, because it is a convenient way to store the discrete model hierarchically. In a hierarchy the discrete model refinement is simple and possible from any previous voxelized scene thanks to the fact that the voxelization algorithms are robust.     

基于Marching Cubes重组的外存模型渐进压缩

外存模型是指其规模远远超出内存容量的海量模型．为提高其存储、传输、显示等操作的效率，对外存模型进行渐进式的压缩是非常重要的．但当前已有的外存模型压缩算法都是单一层次的，不能做到渐进压缩．为此，该文提出一种针对外存模型的渐进压缩方法．能高效地压缩外存模型，并进行多分辨率的传输和显示．该方法首先将外存模型的包围盒空间按照八叉树形式进行剖分和层次化组织，使得最精细层次的各个立方块空间中的局部模型都能完全装入内存进行处理；然后，在各个立方块中对局部的模型进行基于Marching Cubes方式的重新拟合，并在此基础上建立各个局部的自适应八叉树；最后，基于各个局部自适应的八叉树，由粗至细渐进地遍历全局自适应八叉树的各个节点，并利用对内存模型能高效渐进压缩编码的先进方法进行编码压缩．实验表明，该方法对外存模型的压缩比达到了与处理内存模型相似的压缩比．高于目前的外存模型压缩方法，是第一个能渐进压缩外存模型的方法．