A Reparameterisation Based Approach to Geodesic Constrained Solvers for Curve Matching

We present a numerical algorithm for a new matching approach for parameterisation independent diffeomorphic registration of curves in the plane, targeted at robust registration between curves that require large deformations. This condition is particularly useful for the geodesic constrained approach in which the matching functional is minimised subject to the constraint that the evolving diffeomorphism satisfies the Hamiltonian equations of motion; this means that each iteration of the nonlinear optimisation algorithm produces a geodesic (up to numerical discretisation). We ensure that the computed solutions correspond to geodesics in the shape space by enforcing the horizontality condition (conjugate momentum is normal to the curve). Explicitly introducing and solving for a reparameterisation variable allows the use of a point-to-point matching condition. The equations are discretised using the variational particle-mesh method. We provide comprehensive numerical convergence tests and benchmark the algorithm in the context of large deformations, to show that it is a viable, efficient and accurate method for obtaining geodesics between curves.     

基于路径索引的XML小枝模式匹配方法

小枝模式匹配作为XML查询的核心操作,目前在该方面已经提出了一系列有效的实现方法.在总结分析先前各种匹配算法的基础上,提出了一种新的基于路径索引的解决方法TwigFilter,该方法是一个单阶段算法,避免了路径归并.同时,考虑到通常查询中只有少数几个结点是所需的输出结果这一特点,该方法区别输出结点和其他查询结点,保证整个查询处理过程都是根据输出结点进行的.实验结果表明,该算法优于以前的算法,尤其是对查询中只有祖先-后裔关系的表达式更有效.     

一种用于辅助导航的快速图像匹配方法

为了提高辅助导航中多传感器图像匹配的精确性和实时性,首先提取图像的边缘特征,并用3-4距离变换(3-4DT)方法对边缘二值图像进行变换,以变换后的边缘距离图像为匹配特征;针对传统Hausdorff距离的局限性提出了一种融合点集重合数的Hausdorff距离,并以之为相似性度量;搜索策略根据人眼视觉系统的机制采用一种由远到近的分层匹配方法,同时使用一种改进的实数编码遗传算法来加快底层图像匹配的速度。实验结果为平均匹配时间为1283m s,平均误差值为1.036,表明匹配方法能满足导航要求。     

允许错误的并行字符串匹配技术

本文提出了一种允许错误的并行字符串查找技术，通过引入搜索状态向量及字符－模式匹配向量，该技术将字符串匹配比较转化为简单的整数字位运算，通过对字符串方向相反的搜索有效地实现了多处理机对字符串的并行相似检索，文中也给出了并行实现算法，同时分析了算法的复杂性。     

一种稳健的直线提取和匹配算法

在空间机器人遥操作中,需要快速的求解图像的摄像机参数来对操作对象进行三维建模.通过利用匹配直线的对应关系,可以直接求出图像的摄像机参数,而且比用角点匹配求得的结果具有更高的可靠性.现有的直线提取和匹配算法虽然已经有很多,但是大部分都比较耗时,不能满足实时性的要求.针对空间机器人遥操作等实时性较强的应用,提出了一种基于直线支持区域的稳健、快速的直线提取和匹配算法.实验结果表明了该算法的有效性.     

智能型地图匹配综合算法的研究

介绍自行设计的一种依历史轨迹推导的算法,在此基础上针对地图匹配过程中出现的问题,提出一种地图匹配的智能型综合算法,实验证明：该算法是一种精度高、效率好、实用性强的地图匹配算法。     

基于特征点匹配技术的图像检索方法

图像数据的无序激增使得基于内容的图像检索技术成为一个研究热点。为了克服普通颜色特征不考虑颜色的空间分布的缺点,提出了一种多分辨率分块特征点匹配的图像检索技术。同时,还将相关反馈技术融合到多分辨率分块主色算法中以便改善检索效果。实验表明,文中所叙述的方法是比较有效的。     

一种可靠的高分辨率光学卫星遥感影像匹配方法

提出一种基于虚拟交点的高分辨率光学卫星遥感影像自动匹配方法。具体流程包括:(1)初始获取同名点,建立影像局部粗匹配模型;(2)利用同名点构建同名虚拟直线,通过同名虚拟直线形成同名虚拟交点集,并采用局部粗匹配模型进行约束;(3)对候选点集进行特征描述;(4)对特征点利用最小欧式距离准则提取初始同名点;(5)采用RANSAC算法和多项式拟合迭代法剔除误匹配点以获取最终的匹配结果。实验结果表明了本文通过虚拟交点提取同名点的算法,获取了更好的匹配效率和精度。     

Performance Optimization of Switched Systems: A Model Matching Approach

In this paper we consider a prototypical model matching problem where the various mappings involved are systems that switch arbitrarily among n stable linear time-invariant (LTI) systems. The interest is placed on optimizing the worst-case performance of this model matching system over all possible switchings with either l _infin-induced norm or H ₂ norm as the performance criterion. This optimization is performed over all Youla-Kucera parameters that switch causally in time among n stable LTI systems. For the particular setup at hand, it is shown that the optimal Youla-Kucera parameter need not depend on the switching trajectory in the cases of partially matched switching and unmatched switching, and that it can be obtained as an LTI solution to an associated standard l ₁ or H ₂ optimization. In the case of matched switching, two convergent sequences to the optimal solution from above and below are formulated in terms of linear programs and quadratic programs respectively for the l _infin-induced and H ₂ norm optimizations. An approximate solution with any given precision is possible by finite truncation. Applications of these results to sensitivity minimization, linear switched parameter systems, and cooperative control are provided.     

A Line Feature Matching Technique Based on an Eigenvector Approach

In this paper, we propose a new eigenvector-based line feature matching algorithm, which is invariant to the in-plane rotation, translation, and scale. First, in order to reduce the number of possible matches, we use a preliminary correspondence test that generates a set of finite candidate models, by restricting combinations of line features in the input image. This approach resolves an inherent problem relating to ordering and correspondence in an eigenvector/modal approach. Second, we employ the modal analysis, in which the Gaussian weighted proximity matrices for reference and candidate models are constructed to record the relative distance and angle information between line features for each model. Then, the modes of the proximity matrices of the two models are compared to yield the dissimilarity measure, which describes the quantitative degree of the difference between the two models. Experimental results for synthetic and real images show that the proposed algorithm performs matching of the line features with affine variation fast and efficiently and provides the degree of dissimilarity in a quantitative way.     

基于QoS的语义Web服务匹配策略

Web服务技术的迅速发展使得Web服务的应用越来越广泛。因此Web服务的匹配和查找问题成为研究热点。文中引用OWL-S对Web服务进行语义描述,在此基础上增加了对服务QoS的描述。把对Web服务的输入、输出参数的语义描述匹配问题进行转化,可以转为基于领域本体库中相似概念间的语义距离计算,并根据语义距离给出了概念相似度的计算公式。对于基于语义的Web服务发现给出了匹配算法描述。在QoS约束匹配过程中,利用服务性价比的概念,为用户选择最佳性能的Web服务,同时也可以对最终的匹配结果按照请求者的意愿进行排序,以满足请求者不同的需要并使得用户同时可以根据本身需求选择性地使用服务。     

使用社区结构信息的子图匹配算法优化方法*

子图匹配是图数据查询处理技术中的一个重要研究问题。针对现有子图匹配算法运行效率不高且缺乏通用优化方法的现状,提出一种基于社区结构的子图匹配算法优化方法(community structure based subgraph matching optimization method,CSO)。首先,提出两种优化策略,即解析模式图信息以减少子图匹配过程的计算量,以及利用社区结构信息在子图匹配过程中进行剪枝;然后,结合上述两种优化策略提出基于社区结构的子图匹配算法优化方法,并进行了理论分析。真实数据集和合成数据集上的大量实验结果表明,CSO方法能有效减少子图匹配算法的时间开销。同时,不同规模数据集上的实验结果验证了CSO方法良好的可扩展性。     

三维局部相似目标匹配的微分几何方法

提出一种基于高斯曲率和平均曲率的三维局部相似目标匹配方法,首先筛选出待匹配曲面上固有特征相似的点,形成点对集合,然后利用非对称三角形骨架来定位三维曲面,在点对集合中寻找相似三角形对,并导出其空间变换,构成三角形对集合,最后通过得分函数,求出三角形对集合中空间变换的最佳值,得出最佳匹配,实验表明,该方法对三维局部相似目标匹配具有较好的识别效率,针对不规则三维曲面,能够保证较好的匹配速度.     

Learning to Tag and Tagging to Learn: A Case Study on Wikipedia

The problem of semantically annotating Wikipedia inspires a novel method for dealing with domain and task adaptation of semantic taggers in cases where parallel text and metadata are available.     

Approximate Structural Context Matching: An Approach to Recommend Relevant Examples

When coding to an application programming interface (API), developers often encounter difficulties, unsure of which class to subclass, which objects to instantiate, and which methods to call. Example source code that demonstrates the use of the API can help developers make progress on their task. This paper describes an approach to provide such examples in which the structure of the source code that the developer is writing is matched heuristically to a repository of source code that uses the API. The structural context needed to query the repository is extracted automatically from the code, freeing the developer from learning a query language or from writing their code in a particular style. The repository is generated automatically from existing applications, avoiding the need for handcrafted examples. We demonstrate that the approach is effective, efficient, and more reliable than traditional alternatives through four empirical studies     

Using Wikipedia knowledge to improve text classification

Text classification has been widely used to assist users with the discovery of useful information from the Internet. However, traditional classification methods are based on the “Bag of Words” (BOW) representation, which only accounts for term frequency in the documents, and ignores important semantic relationships between key terms. To overcome this problem, previous work attempted to enrich text representation by means of manual intervention or automatic document expansion. The achieved improvement is unfortunately very limited, due to the poor coverage capability of the dictionary, and to the ineffectiveness of term expansion. In this paper, we automatically construct a thesaurus of concepts from Wikipedia. We then introduce a unified framework to expand the BOW representation with semantic relations (synonymy, hyponymy, and associative relations), and demonstrate its efficacy in enhancing previous approaches for text classification. Experimental results on several data sets show that the proposed approach, integrated with the thesaurus built from Wikipedia, can achieve significant improvements with respect to the baseline algorithm.

Space-Time Domain Expansion Approach to VLSI and Its Application to Hierarchical Scene Matching

VLSI technology has recently received increasing attention due to its high performance and high reliability. Designing a VLSI structure systematically for a given task becomes a very important problem to many computer engineers. In this paper, we present a method to transform a recursive computation task into a VLSI structure systematically. The main advantages of this approach are its simplicity and completeness. Several examples, such as vector inner product, matrix multiplication, convolution, comparison operations in relational database and fast Fourier transformation (FFT), are given to demonstrate the transformation procedure. Finally, we apply the proposed method to hierarchical scene matching. Scene matching refers to the process of locating or matching a region of an image with a corresponding region of another view of the same image taken from a different viewing angle or at a different time. We first present a constant threshold estimation for hierarchical scene matching. The VLSI implementation of the hierarchical scene matching is then described in detail.     

语义模型驱动的数据属性匹配技术研究

目前,企业对数据集成的要求逐渐上升到语叉层面。针对数据语叉上的异构问题,提出了一种语义模型驱动的集成方式,并实现了语叉模型应用框架;讨论了框架中语义模型驱动的数据属性匹配技术,该技术用于在语义模型已存在的前提下,通过提供映射的方法实现异构数据到已有模型的映射。