A variational method for contour tracking via covariance matching

This paper presents a novel formulation for contour tracking.We model the second-order statistics of image regions and perform covariance matching under the variational level set framework.Specifically,covariance matrix is adopted as a visual object representation for partial differential equation(PDE) based contour tracking.Log-Euclidean calculus is used as a covariance distance metric instead of Euclidean distance which is unsuitable for measuring the similarities between covariance matrices,because the matrices typically lie on a non-Euclidean manifold.A novel image energy functional is formulated by minimizing the distance metric between the candidate object region and a given template,and maximizing the one between the background region and the template.The corresponding gradient flow is then derived according to a variational approach,enabling partial differential equations(PDEs) based contour tracking.Experiments on several challenging sequences prove the validity of the proposed method.     

A faster divide-and-conquer algorithm for constructing delaunay triangulations

An easily implemented modification to the divide-and-conquer algorithm for computing the Delaunay triangulation ofn sites in the plane is presented. The change reduces its (n logn) expected running time toO(n log logn) for a large class of distributions that includes the uniform distribution in the unit square. Experimental evidence presented demonstrates that the modified algorithm performs very well forn2¹⁶, the range of the experiments. It is conjectured that the average number of edges it creates—a good measure of its efficiency—is no more than twice optimal forn less than seven trillion. The improvement is shown to extend to the computation of the Delaunay triangulation in theL _p metric for 1<p.This research was supported by National Science Foundation Grants DCR-8352081 and DCR-8416190.     

Fuzzy度量空间上映射的又一个不动点定理

继文献〔1〕之后证明了Fuzzy度量空间上映射的又一个不动点定理，使文献〔2〕的§1（3，4）的定理成为本文的特例。     

Multimodel analysis and controller design for nonlinear processes

Multimodel analysis and controller design for nonlinear processes via gap metric is discussed. It is shown that the loop-shaping H_∞ approach can integrate the procedure of selecting operating points and the local controller design. The local controllers can guarantee not only stability but also performance specified by the pre- and/or post-compensators. Thus, at each operating points, local controllers can have similar performance, and the global performance of the system can be predicted.     

Deformation similarity measurement in quasi-conformal shape space

This paper presents a novel approach based on the shape space concept to classify deformations of 3D models. A new quasi-conformal metric is introduced which measures the curvature changes at each vertex of each pose during the deformation. The shapes with similar deformation patterns follow a similar deformation curve in shape space. Energy functional of the deformation curve is minimized to calculate the geodesic curve connecting two shapes on the shape space manifold. The geodesic distance illustrates the similarity between two shapes, which is used to compute the similarity between the deformations. We applied our method to classify the left ventricle deformations of myopathic and control subjects, and the sensitivity and specificity of our method were 88.8% and 85.7%, which are higher than other methods based on the left ventricle cavity, which shows our method can quantify the similarity and disparity of the left ventricle motion well.     

一种面向对象体系结构的度量模型

针对面向对象体系结构的软件系统缺乏有效度量方法的现状,通过行为、逻辑、构件和部署4个互为补充的模型,对面向对象的软件进行了架构分析,并确定了度量数据的采集集合.基于架构分析获得的原始系统数据,吸收快速原型与白盒、黑盒的基本原理,作者提出了一种适合面向确定对象系统的功能-结构-原型度量模型FCPMM(Function Configuration Prototype Metric Model).结合面向对象的基本准则与基本遗传算法,导出了该模型的循环收敛算法,从而可动态求解软件系统的最优状态.最后利用Matlab仿真实例,从度量参数适应度和最佳个体解码值两个方面验证了该算法的可行性.     

对抗样本三元组约束的度量学习算法

针对已有三元组约束的度量学习算法大多利用先验知识构建约束,一定程度上制约了度量学习算法性能的问题,本文借鉴对抗训练中样本扰动的思想,在原始样本附近学习对抗样本以构造对抗三元组约束,基于对抗三元组和原始三元组约束构建了度量学习模型,提出了对抗样本三元组约束的度量学习算法(metric learning algorithm with adversarial sample triples constraints,ASTCML)。实验结果表明,提出的算法既克服了已有固定约束方法受先验知识影响大的问题,也提高了分类精度,说明区分更加难以区分的三元组约束能够提升算法的性能。     

Compositional metric learning for multi-label classification

Multi-label classification aims to assign a set of proper labels for each instance, where distance metric learning can help improve the generalization ability of instance-based multi-label classification models. Existing multi-label metric learning techniques work by utilizing pairwise constraints to enforce that examples with similar label assignments should have close distance in the embedded feature space. In this paper, a novel distance metric learning approach for multi-label classification is proposed by modeling structural interactions between instance space and label space. On one hand, compositional distance metric is employed which adopts the representation of a weighted sum of rank-1 PSD matrices based on component bases. On the other hand, compositional weights are optimized by exploiting triplet similarity constraints derived from both instance and label spaces. Due to the compositional nature of employed distance metric, the resulting problem admits quadratic programming formulation with linear optimization complexity w.r.t. the number of training examples.We also derive the generalization bound for the proposed approach based on algorithmic robustness analysis of the compositional metric. Extensive experiments on sixteen benchmark data sets clearly validate the usefulness of compositional metric in yielding effective distance metric for multi-label classification.     

地物物理量的度量模型及其应用

对地物物理量的度量是获得地物相关信息的重要手段,它是制作地图的依据和信息源泉。基于比较法的地物物理量的度量模型,由度量对象ai、度量基准i0、度量单位Bi和度量结果Qi构成。地物的某一物理性质i∈ai ,存在度量基准i0,i到i0的距离函数d（i,i0）包含度量单位Bi的数量即度量结果Qi。通过对测绘学中的直角坐标、高程、水深、地物的时间坐标（寿命）、质量、温度、卫星激光测距等方面的应用,阐释了地物物理量的度量模型的实用价值和科学解释功能。     

锥度量空间中四个自映射的公共不动点定理

在完备的锥度量空间中讨论了4个自映射的公共不动点定理,其存在性和唯一性得到证明。所得主要结果将锥度量空间中的公共不动点定理进行了推广。