Stereo vision correspondence using a multichannel graph matching technique

A multichannel feature-based stereo vision technique is described in this paper where curve segments are used as the feature primitives in the matching process. Curve segments are extracted by tracking the zero-crossings of the left and right images. The generalized Hough transform of each curve and the curve length are used as a local feature vector in representing the distinctive characteristics of the curve segment. The feature vector of each curve segment in the left image is used as a constraint to find an instance of the same curve segment in the right image. The epipolar constraint on the centroids of the curve segment is used to limit the searching space in the right image.

A relational graph is formed from the left image by treating the centroids of the curve segments as the nodes of the graph. The local features of the curve segments are used to represent the local properties of the nodes, and the relationship between the nodes represents the structural properties of the objects in the scene. A similar graph is also formed from the right image curve segments. A graph isomorphism is then formed between the two graphs by using the epipolar constraint on the centroids, the local properties of the nodes, node assignment and the structural relationship (compatibility) between the nodes.     

基于二分图的故障规则匹配优化算法

针对传统的基于相似度的故障规则匹配方法中未考虑输入条件与规则前件的整体匹配程度问题,采用二分图最优匹配方法对匹配过程进行优化,提出一种基于二分图的故障规则匹配优化算法,并将其应用于故障诊断推理．实例分析表明,与其他相似度匹配算法相比,所提出的方法有效提高了规则匹配的准确率,而且降低了时间消耗．     

基于谱图理论的特征匹配方法研究和改进

图像匹配问题是计算机视觉领域的一个基本问题,广泛地应用于很多领域,如:模式识别,自动导航,医学诊断,计算机视觉,图像三维重构等领域。将所研究的问题转化为数学问题,再利用数学工具解决这一问题,成为当今研究的一种重要手段。在这里,将图像匹配中的图像转化为数学-图论中的图,利用谱图理论解决图像匹配问题,从而形成了一类比较流行而新颖的方法,针对这一方法进行了较为系统的探究并做出了改进。     

二部图最大匹配问题的分层网络优化模型

为解决二部图最大匹配问题,提出了分层网络及网络逆序的概念,在此基础上建立了一种分层网络优化模型及其算法。给出了算法的思想、步骤、实例、时间复杂度分析,概述了求解二部图最大匹配问题的常见算法,与分层网络优化算法进行比较。实验验证,算法可读性强,易于理解和操作,在解决大规模二部图最大匹配问题时具有良好的性能。     

基于轮廓线匹配的二维重迭物体的识别

本文提出一种基于轮廓线匹配的二维重迭物体的识别算法,并采用一种点模式匹配的快速算法进行特征点序列的匹配,通过引进形状移位数的概念和利用问题中的各种约束条件,提高了物体识别速度.     

异构图形数据的近似语义匹配技术研究

以流程工厂协同设计应用为背景,提出基于允许误差的最大语义图匹配（MSMGE）算法的异构图形数据近似语义匹配模型。利用类无向图来描述2D和3D异构图形数据的工程属性和拓扑关系,消除了图形信息的异构性,并建立各种类实体的属性标签词典来消除2D和3D属性信息的异构性,用语义表达式来表示类无向图顶点和边的语义关系,将异构图形匹配转化为近似语义图匹配。通过基于工程语义对类无向图进行语义分割和基于最大公共序列算法的语义表达式比较、语义规整和语义裁剪等方法,降低了匹配搜索空间,提高了近似语义图匹配效率,实现了近似语义图匹配判断。该研究已经在流程工厂设计软件中得到较好地应用。     

Three-Dimensional Reconstruction of Points and Lines with Unknown Correspondence across Images

Three-dimensional reconstruction from a set of images is an important and difficult problem in computer vision. In this paper, we address the problem of determining image feature correspondences while simultaneously reconstructing the corresponding 3D features, given the camera poses of disparate monocular views. First, two new affinity measures are presented that capture the degree to which candidate features from different images consistently represent the projection of the same 3D point or 3D line. An affinity measure for point features in two different views is defined with respect to their distance from a hypothetical projected 3D pseudo-intersection point. Similarly, an affinity measure for 2D image line segments across three views is defined with respect to a 3D pseudo-intersection line. These affinity measures provide a foundation for determining unknown correspondences using weighted bipartite graphs representing candidate point and line matches across different images. As a result of this graph representation, a standard graph-theoretic algorithm can provide an optimal, simultaneous matching and triangulation of points across two views, and lines across three views. Experimental results on synthetic and real data demonstrate the effectiveness of the approach.An erratum to this article can be found at     

Correspondence matching using kernel principal components analysis and label consistency constraints

This paper investigates spectral approaches to the problem of point pattern matching. We make two contributions. First, we consider rigid point-set alignment. Here we show how kernel principal components analysis (kernel PCA) can be effectively used for solving the rigid point correspondence matching problem when the point-sets are subject to outliers and random position jitter. Specifically, we show how the point- proximity matrix can be kernelised, and spectral correspondence matching transformed into one of kernel PCA. Second, we turn our attention to the matching of articulated point-sets. Here we show label consistency constraints can be incorporated into definition of the point proximity matrix. The new methods are compared to those of Shapiro and Brady and Scott and Longuet-Higgins, together with multidimensional scaling. We provide experiments on both synthetic data and real world data.     

Cell tracking in microscopic video using matching and linking of bipartite graphs

Automated visual tracking of cells from video microscopy has many important biomedical applications. In this paper, we track human monocyte cells in a fluorescent microscopic video using matching and linking of bipartite graphs. Tracking of cells over a pair of frames is modeled as a maximum cardinality minimum weight matching problem for a bipartite graph with a novel cost function. The tracking results are further refined using a rank-based filtering mechanism. Linking of cell trajectories over different frames are achieved through composition of bipartite matches. The proposed solution does not require any explicit motion model, is highly scalable, and, can effectively handle the entry and exit of cells. Our tracking accuracy of (97.97 ± 0.94)% is superior than several existing methods [(95.66 ± 2.39)% [11], (94.42 ± 2.08)% [20], (81.22 ± 5.75)% [13], (78.31 ± 4.70)% [14]] and is highly comparable (98.20 ± 1.22)% to a recently published algorithm [26].     

双目视觉的匹配算法综述

双目视觉是获取对现实世界立体感知的重要方法,在自动驾驶等领域得到了普遍 的应用。立体匹配是实现双目感知的前提,该算法对左右摄像机拍摄的照片进行像素级的匹配, 生成稠密视差图,从而获取了三维坐标信息。概述了立体匹配算法近 20 年来的发展过程,围绕 基于人工特征和深度学习两个方向进行了综述,对算法实现过程中的代价计算、代价聚合、视 差计算和视差求精进行分析讨论,评估了算法的准确性和时间复杂度。最后总结了立体匹配算 法面对的挑战和对未来发展的展望。     

三维图匹配算法

目的 现有的图匹配算法大多应用于二维图像,对三维图像的特征点匹配存在匹配准确率低和计算速度慢等问题。为解决这些问题,本文将分解图匹配算法扩展应用在了三维图像上。方法 首先将需要匹配的两个三维图像的特征点作为图的节点集;再通过Delaunay三角剖分算法,将三维特征点相连,则相连得到的边就作为图的边集,从而建立有向图;然后,根据三维图像的特征点构建相应的三维有向图及其邻接矩阵;再根据有向图中的节点特征和边特征分别构建节点特征相似矩阵和边特征相似矩阵;最后根据这两个特征矩阵将节点匹配问题转化为求极值问题并求解。结果 实验表明,在手工选取特征点的情况下,本文算法对相同三维图像的特征点匹配有97.56%的平均准确率;对不同三维图像特征点匹配有76.39%的平均准确率;在三维图像有旋转的情况下,有90%以上的平均准确率;在特征点部分缺失的情况下,平均匹配准确率也能达到80%。在通过三维尺度不变特征变换（SIFT）算法得到特征点的情况下,本文算法对9个三维模型的特征点的平均匹配准确率为98.78%。结论 本文提出的基于图论的三维图像特征点匹配算法,经实验结果验证,可以取得较好的匹配效果。     

基于二分图极大权值匹配的SOC故障定位算法研究*

针对故障传播给故障定位带来的影响,考虑SOC功能测试系统中的故障源和故障事件之间的不确定性,提出一种基于二分图的故障定位算法。首先从SOC中抽象出特定的硬件模块,由这些模块构成故障源。然后故障源结合相应的故障事件组合成二分图,在二分图的基础上生成一种适用于SOC故障定位的故障传播模型(Fault Propagation Model,FPM)。最后将SOC故障定位的问题转化成二分图极大权值匹配的求解问题,从概率上保证结果的正确性。实验结果表明,故障定位准确率提高了0~21%,误报率下降了0~15%,更加适用于小型系统的故障定位。     

基于稳定匹配的电子中介匹配研究

介绍了稳定性双边匹配的概念,概括了Gale-Sharply和H-R算法求解1-1和1-k的计算过程.考虑商品的多属性,给出了交易者按综合满意程度对满足自己约束对方的排序计算方法.将Gale-Sharply和H-R算法从理论上扩展到"p-k"情况,用来解决电子中介处理稳定的多对多双边匹配问题.最后证明了扩展算法所得结果的稳定性,并给出了算例.     

基于边映射表连接的匹配算法

针对面向语义网络图匹配的特殊性, 在基于状态回溯搜索算法的基础上提出一种新的称为基于边映射表连接的匹配算法, 利用语义网络图的有向性, 将图匹配问题转换为对搜索路径的规划, 并采用深度优先算法形成搜索步, 同时对目标图的所有边建立索引, 加快以边匹配为中心形成边映射表的过程, 最后对边映射表进行连接形成结果集。在真实数据集上的实验结果表明, 该算法具有较高的执行效率。     

图匹配算法激光扫描点云树干分割

目的 移动激光扫描系统能够成功采集丰富的城市行道树侧边信息,然而由于点云数据规模大、密度欠均匀和噪声多等原因,导致行道树的提取精度和效率偏低。为此,本文提出一种基于层次聚类的算法从移动激光扫描点云中提取树干。方法 采用自下而上的聚类策略合并目标区域,基于点云间欧氏距离和点云的局部主方向计算聚类所需的邻近矩阵,通过构造能量函数评估不同的簇合并方案,将能量函数最小化问题转换为计算二分图匹配问题,求解二分图的最小代价完美匹配获得全局最优的层次聚类。结果 实验在公开的巴黎场景数据集与自采集的南京黄埔路场景数据集上进行测试,本文提出的自下向上的聚类算法成功地从点云中提取出树干和主要树枝点,其中提取树干的平均正确率、完整率和F-score分别为98.5%、94.8%和0.97,与其他算法中最好的实验结果对比,分别提高了1.0%、0.6%和0.02。结论 实验结果表明,本文算法通过优化层次聚类中的簇合并,可以有效减少聚类中的“过分割”和“欠分割”,提高点云中树干的分割精度与效率。     

A Polynomial-Time Algorithm for Memory Space Reduction

Reducing memory space requirement is important to many applications. For data-intensive applications, it may help avoid executing the program out-of-core. For high-performance computing, memory space reduction may improve the cache hit rate as well as performance. For embedded systems, it can reduce the memory requirement, the memory latency and the energy consumption. This paper investigates program transformations which a compiler can use to reduce the memory space required for storing program data. In particular, the paper uses integer programming to model the problem of combining loop shifting, loop fusion and array contraction to minimize the data memory required to execute a collection of multi-level loop nests. The integer programming problem is then reduced to an equivalent network flow problem which can be solved in polynomial time.     

Robust Surface Fitting from Two Views using Restricted Correspondence

The restricted correspondence problem is the task of solving the classical stereo correspondence problem when the surface being observed is known to belong to a family of surfaces that vary in a known way with one or more parameters. Under this constraint the surface can be extracted far more robustly than by classical stereo applied to an arbitrary surface, since the problem is solved semi-globally, rather than locally for each epipolar line. Here, the restricted correspondence problem is solved for two examples, the first being the extraction of the parameters of an ellipsoid from a calibrated stereo pair. The second example is the estimation of the osculating paraboloid at the frontier points of a convex object.

Maximal matching polytope in trees

Given a weighted simple graph, the minimum weighted maximal matching (MWMM) problem is the problem of finding a maximal matching of minimum weight. The MWMM problem is NP-hard in general, but is polynomial-time solvable in some special classes of graphs. For instance, it has been shown that the MWMM problem can be solved in linear time in trees when all the edge weights are equal to one. In this paper, we show that the convex hull of the incidence vectors of maximal matchings (the maximal matching polytope) in trees is given by the polytope described by the linear programming relaxation of a recently proposed integer programming formulation. This establishes the polynomial-time solvability of the MWMM problem in weighted trees. The question of whether or not the MWMM problem can be solved in linear time in weighted trees is open.     

双摄象头三维视觉系统

本文介绍了一种较实用的双摄象头三维视觉系统.主要讨论了视场内具有六个自由度物体的定位问题.系统以Frei和Chen方法抽取边缘,并运用了非均匀量化和预加重技术.采用了改进的Moravec兴趣算子法,实现了特征点的自动抽取.基于边缘的序贯分层配准法大大缩短了配准时间.在用三维数据获取物体姿态时.根据刚体运动总结的规则解决了工作特征点和模型点匹配时的组合爆炸问题和多义性问题.     

Structure and attribute index for approximate graph matching in large graphs

The increasing popularity of graph data in various domains has lead to a renewed interest in developing efficient graph matching techniques, especially for processing large graphs. In this paper, we study the problem of approximate graph matching in a large attributed graph. Given a large attributed graph and a query graph, we compute a subgraph of the large graph that best matches the query graph. We propose a novel structure-aware and attribute-aware index to process approximate graph matching in a large attributed graph. We first construct an index on the similarity of the attributed graph, by partitioning the large search space into smaller subgraphs based on structure similarity and attribute similarity. Then, we construct a connectivity-based index to give a concise representation of inter-partition connections. We use the index to find a set of best matching paths. From these best matching paths, we compute the best matching answer graph using a greedy algorithm. Experimental results on real datasets demonstrate the efficiency of both index construction and query processing. We also show that our approach attains high-quality query answers.