网格模型的局部编辑算法

提出一种新的网格模型局部编辑算法，该算法可以精确地控制变形区域的大小、边界和变形点的位移，克服了FFD及其改进算法的缺点．首先交互地定义一个附着在模型表面的控制网格；然后建立模型变形区域与控制网格间点的映射，再依据变形要求来编辑控制网格；最后根据映射关系反算出模型变形区域点的新位置．控制网格可以是参数曲面的控制网格，也可采用一般三角网格或预先定义的网格模板．为达到精确变形的目的，对模型与控制网格重叠的区域进行自适应细分．该算法计算简便、易于实现，并能达到很好的效果．     

基于细分曲面的泊松网格编辑

针对具有丰富几何细节的三维网格模型,基于直接坐标操纵的传统编辑算法在编辑过程中不可避免地存在细节特征无法得到有效保持的问题.综合基于细分曲面的空间变形方法以及微分域网格编辑二者优势,提出一种基于细分曲面的泊松网格编辑方法.首先建立待变形网格模型的包围网格,以包围网格所决定的细分曲面构造变形控制曲面;然后根据用户变形意图操纵包围网格,将对应细分曲面变化信息转化为对网格模型泊松梯度场的改变;最后根据变化后的梯度场重建网格模型.文中方法交互简单、直观,具有多分辨率编辑的优势,可以有效地保持网格模型的细节特征.丰富的变形实例证明了该方法的有效性和可行性.     

一种基于约束特征的网格编辑技术

为了改进自由变形技术在用户交互和编辑灵活性的不足,提出了一种直观的交互式网格模型编辑技术,该技术可以根据不同的约束变形特征、封闭的变形边界以及编辑参考曲线来完成网格模型的编辑,并且为了模型的平滑和自然,采用了自适应细分策略。实验证明,该方法简便直观,有良好的交互性,并能得到很好的编辑结果。此技术可以方便地应用于CAD/CAM和计算机动画系统中。     

直接点操作的人脸变形与动画

自由变形（FFD）是计算机人脸动画和表情编辑的常用方法,但对控制点的反求和变形结果的不直观是该方法的不足。提出了基于直接点操作网格的变形方法,通过鼠标的交互编辑,可以直接得到可控制的变形结果。试验结果表明该方法简单有效。     

基于层次B样条的网格模型变形技术

针对常用的网格模型提出了一个基于层次B样条控制的三维网格空间变形框架．首先由用户交互地选取编辑区域，由程序完成编辑区域的参数化和均匀重采样；然后用层次B样条光顺拟合这些均匀采样点，所得的R样条曲面作为网格模型的基曲面，计算待编辑区域中网格顶点相对该B样条基曲面的局部坐标，该局部坐标平移、旋转不变，可视为模型的内蕴几何特征，并作为变形操作中的不变量．用户通过编辑层次B样条基曲面或者直接编辑三维网格模型，可实现多分辨率变形．实验结果表明：该方法操作直观方便，无论对整体还是局部变形，都能取得可控、可靠的变形效果，且采刚B样条曲面的控制手段易于与已有的造型系统合成．     

基于曲率流的点模型编辑方法*

为了对点模型表面进行保细节的自由形状编辑,提出了一种基于曲率流的点模型形状编辑方法。该方法定义了基于平均曲率流的光顺算子,通过此光顺算子获得点模型不同光滑程度的曲面表示。运用对应曲面上点之间的向量差进行相应几何细节的抽取,在相邻的曲面表示之间将几何细节剥离出来。用户可以在不同的曲面上进行自由形状编辑,而无须关心几何细节。在变形后的曲面上再将相应的几何细节映射回去,实现对模型保细节的变形。实验结果表明该方法是一种有效的点模型造型算法,在变形的同时,有效地保持了模型表面的细节特征。     

基于曲率流的点模型编辑方法*

为了对点模型表面进行保细节的自由形状编辑,提出了一种基于曲率流的点模型形状编辑方法。该方法定义了基于平均曲率流的光顺算子,通过此光顺算子获得点模型不同光滑程度的曲面表示。运用对应曲面上点之间的向量差进行相应几何细节的抽取,在相邻的曲面表示之间将几何细节剥离出来。用户可以在不同的曲面上进行自由形状编辑,而无须关心几何细节。在变形后的曲面上再将相应的几何细节映射回去,实现对模型保细节的变形。实验结果表明该方法是一种有效的点模型造型算法,在变形的同时,有效地保持了模型表面的细节特征。     

三维网格的交互式编辑

在曲面造型系统中,如何方便地修改和交互地编辑曲面模型是一个关键问题。提出了一种基于小波多分辨率分析的交互式编辑方法。首先通过小波多分辨率分析,将复杂网格简化成各种分辨率;然后再通过Dijkstra最短路径算法和宽度遍历方法选取待编辑区域;最后,基于三维图形的几何变换方法,对选取的区域进行交互式编辑,进而合并之,并恢复到原始分辨率。实验结果表明,该方法主要特点是操作直观、方便、快速。     

网格变形综述

网格变形作为一种几何模型交互编辑技术在几何建模和计算机动画中具有重要价值。近年来,保细节的网格变形特别是微分域网格变形一直得到国内外研究人员的高度关注。从骨骼变形、曲面变形、空间变形3个方面,结合近年来网格变形领域的最新研究进展,通过对各种典型的网格变形算法的算法思想、特点、局限性的描述和比较,提供该领域研究现状的系统综述。并对网格变形的研究趋势进行了展望。     

基于几何特征的三维模型变形与编辑*

在三维计算的基础上针对三维颅面模型,提出了一种基于几何特征的三维模型变形与编辑算法。该算法采用迭代过程,即每进行一次变形便可以重新计算调整后的颅面几何特征值,如果满足需要则退出编辑并保存模型;否则继续变形,直到得到满意的三维模型为止。在局部变形中,为了弥补自由变形技术在变形控制和用户交互方面的不足,对点约束局部变形算法进行了改进。实验证明,该算法实现简单,且具有良好的交互性,变形效果良好。     

Material-aware differential mesh deformation using sketching interface

In this paper, we present a material-aware mesh deformation method using a sketching interface. Guided by user-specified material properties, our method can deform the surface mesh in a non-uniform way, while previous deformation techniques are mainly designed for uniform materials. The non-uniform deformation is achieved by material-dependent gradient field manipulation and Poisson-based reconstruction. Compared with previous material-oblivious deformation techniques, our method supplies better control of the deformation process and can generate more realistic results. We propose a novel detail representation that transforms geometric details between successive surface levels as a combination of dihedral angles and barycentric coordinates. This detail representation is similarity-invariant and fully compatible with material properties. Based on these two methods, we implement a multi-resolution deformation tool, allowing the user to edit a mesh inside a hierarchy in a material-aware manner. We demonstrate the effectiveness and robustness of our methods by several examples with real-world data.     

Automatic learning of cost functions for graph edit distance

Graph matching and graph edit distance have become important tools in structural pattern recognition. The graph edit distance concept allows us to measure the structural similarity of attributed graphs in an error-tolerant way. The key idea is to model graph variations by structural distortion operations. As one of its main constraints, however, the edit distance requires the adequate definition of edit cost functions, which eventually determine which graphs are considered similar. In the past, these cost functions were usually defined in a manual fashion, which is highly prone to errors. The present paper proposes a method to automatically learn cost functions from a labeled sample set of graphs. To this end, we formulate the graph edit process in a stochastic context and perform a maximum likelihood parameter estimation of the distribution of edit operations. The underlying distortion model is learned using an Expectation Maximization algorithm. From this model we finally derive the desired cost functions. In a series of experiments we demonstrate the learning effect of the proposed method and provide a performance comparison to other models.     

基于基本操作序列的编辑距离顺序验证

两字符串的编辑距离是从一个串转换到另一个串所需要的最少基本操作数。编辑距离广泛应用于字符串近似匹配、字符串相似连接等领域。动态规划法利用编辑距离矩阵来计算两个串的编辑距离,需要计算矩阵中的所有元素,时间效率低。改进的方法改变了矩阵中元素的计算次序,减少了需要比对的元素,但仍需要比对一半以上的元素,时间效率还有待提高。提出基于基本操作序列的编辑距离顺序验证方法。首先,分析了基本操作序列的可列性,给出了列举基本操作序列的方法。然后依次顺序验证基本操作数从小到大的基本操作序列直到某一序列通过验证,得到其编辑距离。在阈值为2的字符串近似搜索实验中发现,所提方法比动态规划类方法具有更高的效率。     

一种有效的编辑距离和编辑路径求解技术

给定字符串Ｔ．Ｐ，将Ｔ转换成Ｐ所需的插入，删除，替代序列称为Ｔ到Ｐ的编辑路径，其最短编辑路径所需的插入，删除替代总数称为Ｔ到Ｐ的编辑距离，本文提出一种有效的编辑距离和编辑路径求解技术，该技术首先通过一有效的字符串相似匹配算法计算出编辑距离，而后仅通过简单的二进制字位运算正确计算出编辑路径。     

利用NetMeeting实现多媒体同步协同新闻采编

文章介绍了利用NetMeeting的应用程序共享功能及多媒体功能在新闻采编系统中实现多媒体同步协同编辑的思想,并结合一个具体的实例给出了实现的方法。     

A relation between edit distance for ordered trees and edit distance for Euler strings

We consider a relationship between the unit cost edit distance for two rooted ordered trees and the unit cost edit distance for the corresponding Euler strings. We show that the edit distance between trees is at least half of the edit distance between the Euler strings and is at most 2h+1 times the edit distance between the Euler strings, where h is the minimum height of two trees. The result can be extended for more general cost functions.     

基于uClinux嵌入式操作系统的串行接口电路设计

近年,嵌入式系统的设计被应用到越来越多的领域,但由于嵌入式操作系统的应用是与硬件设计紧密相关的,因此,根据不同的应用环境,需对uClinux内核源码进行适当的修改。文中根据实际工程设计案例,对串行接口电路的硬件设计与uClinux内核的裁剪进行了详细的描述,为uClinux操作系统在嵌入式领域的应用起到了一定的借鉴作用。     

A novel edge-centric approach for graph edit similarity computation

Graph similarity is an important notion with many applications. Graph edit distance is one of the most flexible graph similarity measures available. The main problem with this measure is that in practice it can only be computed for small graphs due to its exponential time complexity. This paper addresses the high complexity of graph edit distance computations. Specifically, we present CSI_GED, a novel edge-centric approach for computing graph edit distance through common sub-structure isomorphisms enumeration. CSI_GED utilizes backtracking search combined with a number of heuristics to reduce memory requirements and quickly prune away a large portion of the mapping search space. Experiments show that CSI_GED is highly efficient for computing graph edit distance; it outperforms the state-of-the-art methods by over three orders of magnitude. It also shows that CSI_GED scales the computation gracefully to larger and distant graphs on which current methods fail to run. Moreover, we evaluated CSI_GED as a stand-alone graph edit similarity search query method. The experiments show that CSI_GED is effective and scalable, and outperforms the state-of-the-art indexing-based methods by over two orders of magnitude.     

The approximate swap and mismatch edit distance

There is no known algorithm that solves the general case of the approximate edit distance problem, where the edit operations are insertion, deletion, mismatch, and swap, in time o(nm), where n is the length of the text and m is the length of the pattern.In the effort to study this problem, the edit operations have been analyzed independently. Karloff [10] showed an algorithm that approximates the edit distance problem with only the mismatch operation in time . Amir et al. [4] showed that if the only edit operations allowed are swap and mismatch, then the exact edit distance problem can be solved in time .In this paper, we discuss the problem of approximate edit distance with swap and mismatch. We show a randomized time algorithm for the problem. The algorithm guarantees an approximation factor of (1+?) with probability of at least .     

Faster algorithms for guided tree edit distance

The guided tree edit distance problem is to find a minimum cost series of edit operations that transforms two input forests F and G into isomorphic forests F^′ and G^′ such that a third input forest H is included in F^′ (and G^′). The edit operations are relabeling a vertex and deleting a vertex. We show efficient algorithms for this problem that are faster than the previous algorithm for this problem of Peng and Ting [Z. Peng, H. Ting, Guided forest edit distance: Better structure comparisons by using domain-knowledge, in: Proc. 18th Symposium on Combinatorial Pattern Matching (CPM), 2007, pp. 28-39].