保持特征的网格修补

提出了一种恢复缺失尖锐特征的网格修补算法。首先对网格顶点建立自适应的八叉树,采用分段二次多项式对网格空洞周围顶点进行拟合。而在尖锐特征处周围,则采用两个或者多个系数不同的二次多项式函数,分别进行拟合,从而获取原始网格所在曲面的尖锐特征边和角。利用扩展的Marching Cube方法获得空洞处的三角网格面片,并和原始网格模型缝合。最后,对于空洞处的网格面片,进行增强特征处理,消除锯齿状网格,获得清晰的尖锐特征。实验结果表明,该方法达到了预期的良好效果。     

Completion and Reconstruction with Primitive Shapes

We consider the problem of reconstruction from incomplete point-clouds. To find a closed mesh the reconstruction is guided by a set of primitive shapes which has been detected on the input point-cloud (e.g. planes, cylinders etc.). With this guidance we not only continue the surrounding structure into the holes but also synthesize plausible edges and corners from the primitives' intersections. To this end we give a surface energy functional that incorporates the primitive shapes in a guiding vector field. The discretized functional can be minimized with an efficient graph-cut algorithm. A novel greedy optimization strategy is proposed to minimize the functional under the constraint that surface parts corresponding to a given primitive must be connected. From the primitive shapes our method can also reconstruct an idealized model that is suitable for use in a CAD system.     

快速结构化图像修补

图像修补的目的是对图像中缺失的区域进行修复,或是将图像中的物体抠去并进行背景填充,以取得融合到难以用肉眼分辨的效果。在图像修补的过程中,较大的结构信息是修补的难点。为此提出了一种快速结构化的图像修补算法,该方法将图像修补分为结构修补与纹理填充两个部分,即在用户指定待修补区域与结构曲线之后,首先定义全局最优化能量函数,并用动态规划与置信度传播的算法将其最小化来完成结构修补;然后对剩余的待修补区域通过按行扫描来进行纹理填充,其中对于边界处的点是使用基于样本的修补算法,而对于待修补区域内部的点,则使用快速的加权Ashikhmin-WL算法,扫描完成后输出修补后的图像;最后实现了一个快速结构化图像修补系统,并给出一些实验结果,从实验结果中可以看到,该方法的修补流程与算法是有实际应用价值的。     

空间完备性理论及其测试

证明和测试是验证规格说明是否正确的2种方法，两者互为补充。针对软件规格说明难以证明的问题，提出对状态空间进行完备性测试的理论。采用构造函数和受限状态空间的概念，讨论用于测试Z规格说明语言初始状态存在性的方法，通过实例证明该方法的可行性。     

矩阵补全模型及其算法研究综述

近年来,随着压缩感知技术在信号处理领域的巨大成功,由其衍生而来的矩阵补全技术也日益成为机器学习领域的研究热点,诸多研究者针对矩阵补全问题展开了大量卓有成效的研究.为了更好地把握矩阵补全技术的发展规律,促进矩阵补全理论与工程应用相结合,本文针对矩阵补全模型及其算法进行综述.首先对矩阵补全技术进行溯源,介绍了从压缩感知到矩阵补全的自然演化历程,指出压缩感知理论的发展为矩阵补全理论的形成奠定了基础;其次从非凸非光滑秩函数松弛的角度将现有矩阵补全模型进行分类,旨在为面向具体应用的矩阵补全问题建模提供思路;接着综述了适用于矩阵补全模型求解的代表性优化算法,其目的在于从本质上理解各种矩阵补全模型优化技巧,从而有利于面向应用问题的矩阵补全新模型求解;最后分析了矩阵补全模型及其算法目前存在的问题,提出了这些问题可能的解决思路,并对未来研究方向进行了展望.     

空间完备性理论及其测试

证明和测试是验证规格说明是否正确的2种方法,两者互为补充.针对软件规格说明难以证明的问题,提出对状态空间进行完备性测试的理论.采用构造函数和受限状态宅间的概念,讨论用于测试z规格说明语言初始状态存在性的方法,通过实例证明该方法的可行性.     

Strategy Compliant Multi-Threaded Term Completion

We report on the design, implementation, and performance,of the parallel term-rewriting system PaReDuX.We discuss the parallelization of three term completion procedures: Knuth-Bendix completion, completion modulo AC, and unfailing completion. Our parallelization is strategy-compliant, i.e., the parallel code performs exactly the same work as the sequential code, but the work load is shared by many processors. PaReDuX is designed for shared memory parallel architectures, such as multi-processor workstations, where it shows good performance on a variety of examples.     

智能代码补全研究综述

代码补全(code completion)是自动化软件开发的重要功能之一,是大多数现代集成开发环境和源代码编辑器的重要组件.代码补全提供即时类名、方法名和关键字等预测,辅助开发人员编写程序,直观提高软件开发效率.近年来,开源软件社区中源代码和数据规模不断扩大,人工智能技术取得了卓越进展,这对自动化软件开发技术产生了极大的促进作用.智能代码补全(intelligent code completion)根据源代码建立语言模型,从语料库学习已有代码特征,根据待补全位置的上下文代码特征在语料库中检索最相似的匹配项进行推荐和预测.相对于传统代码补全,智能代码补全凭借其高准确率、多补全形式、可学习迭代的特性成为软件工程领域的热门方向之一.研究者们在智能代码补全方面进行了一系列研究,根据这些方法如何表征和利用源代码信息的不同方式,可以将它们分为基于编程语言表征和基于统计语言表征两个研究方向,其中,基于编程语言表征又分为标识符序列、抽象语法树、控制/数据流图这3个类别,基于统计语言表征又分为N-gram模型、神经网络模型这2个类别.从代码表征的角度入手,对近年来代码补全方法研究进展进行梳理和总结,主要...     

Euler Spiral for Shape Completion

In this paper we address the curve completion problem, e.g., the geometric continuation of boundaries of objects which are temporarily interrupted by occlusion. Also known as the gap completion or shape completion problem, this problem is a significant element of perceptual grouping of edge elements and has been approached by using cubic splines or biarcs which minimize total curvature squared (elastica), as motivated by a physical analogy. Our approach is motivated by railroad design methods of the early 1900's which connect two rail segments by transition curves, and by the work of Knuth on mathematical typography. We propose that in using an energy minimizing solution completion curves should not penalize curvature as in elastica but curvature variation. The minimization of total curvature variation leads to an Euler Spiral solution, a curve whose curvature varies linearly with arclength. We reduce the construction of this curve from a pair of points and tangents at these points to solving a nonlinear system of equations involving Fresnel Integrals, whose solution relies on optimization from a suitable initial condition constrained to satisfy given boundary conditions. Since the choice of an appropriate initial curve is critical in this optimization, we analytically derive an optimal solution in the class of biarc curves, which is then used as the initial curve. The resulting interpolations yield intuitive interpolation across gaps and occlusions, and are extensible, in contrast to the scale-invariant version of elastica. In addition, Euler Spiral segments can be used in other applications of curve completions, e.g., modeling boundary segments between curvature extrema or modeling skeletal branch geometry.     

Completion for Multiple Reduction Orderings

We present a completion procedure (called MKB) that works for multiple reduction orderings. Given equations and a set of reduction orderings, the procedure simulates a computation performed by the parallel processes each of which executes the standard completion procedure (KB) with one of the given orderings. To gain efficiency, however, we develop new inference rules working on objects called nodes, which are data structures consisting of a pair s : t of terms associated with the information to show which processes contain the rule s t (or t s) and which processes contain the equation s t. The idea is based on the observation that some inferences made in different processes are often closely related, so we can design inference rules that simulate these inferences all in a single operation. Our experiments show that MKB is significantly more efficient than the naive simulation of parallel execution of KB procedures, when the number of reduction orderings is large enough. We also present an extension of this technique to the unfailing completion for multiple reduction orderings, which is useful in various areas of automated reasoning, including equational theorem proving.     

A Categorical Critical-pair Completion Algorithm

We introduce a general critical-pair/completion algorithm, formulated in the language of category theory. It encompasses the Knuth–Bendix procedure for term rewriting systems (also modulo equivalence relations), the Gröbner basis algorithm for polynomial ideal theory, and the resolution procedure for automated theorem proving. We show how these three procedures fit in the general algorithm, and how our approach relates to other categorical modeling approaches to these algorithms, especially term rewriting.     

Completion of overdetermined parabolic PDEs

In this paper we apply methods of commutative algebra to analysis of systems of PDEs. More precisely, we show that systems which are parabolic in a generalized sense are equivalent to certain completed systems which are parabolic in the standard sense. We also propose a constructive method for getting this completion, and Gröbner basis methods, via symbol modules of the systems, play a central role in practical computations. Moreover, we can easily construct systems which are not parabolic in the generalized sense but nevertheless become parabolic when completed.     

Proof Lengths for Equational Completion

We first show that ground term-rewriting systems can be completed in a polynomial number of rewriting steps, if the appropriate data structure for terms is used. We then apply this result to study the lengths of critical pair proofs in non-ground systems, and obtain bounds on the lengths of critical pair proofs in the non-ground case. We show how these bounds depend on the types of inference steps that are allowed in the proofs.     

Note on curve and surface energies

Energies of curves and surfaces play a prominent role as fairness functionals in geometric modeling and computer-aided geometric design. In this paper we present a particular discrete surface energy which is expressible in terms of curve energies, and thus particularly appropriate for digital elevation data smoothing with tolerance zone constraints. We also discuss other geometrically meaningful surface energies in the context of invariant theory.     

基于低秩表示与矩阵填充的人脸识别方法

基于回归分析的人脸识别方法在处理不完备数据矩阵时,先对矩阵进行填充,再使用人脸识别方法,因此会降低分类性能.为了更有效地执行关于不完备数据的识别,文中将低秩矩阵填充和低秩表示学习整合在同一个模型,提出基于低秩表示和低秩矩阵填充的人脸识别方法.通过最小化表示系数和矩阵秩交替计算样本低秩表示系数矩阵和恢复矩阵缺失项,再使用最近邻分类器实现分类.在一些公开人脸数据集上的实验表明,在训练样本矩阵元素随机缺失时,文中方法可以有效提高识别精度及降低填充误差.     

完成端口模型的使用与分析

完成端口是一种复杂的Win32内核对象。应用程序可以用完成端口管理线程池为大量的异步I/O请求提供服务,而不必为每个I/O请求分别创建服务线程。完成端口模型用于开发服务器应用程序,以提供优良的伸缩性和获得最好的系统性能。本文构建了一个基本的网络服务器程序框架,对完成端口模型的用法进行阐述与分析。     

Sparse and Truncated Nuclear Norm Based Tensor Completion

One of the main difficulties in tensor completion is the calculation of the tensor rank. Recently a tensor nuclear norm, which is equal to the weighted sum of matrix nuclear norms of all unfoldings of the tensor, was proposed to address this issue. However, in this approach, all the singular values are minimized simultaneously. Hence the tensor rank may not be well approximated. In addition, many existing algorithms ignore the structural information of the tensor. This paper presents a tensor completion algorithm based on the proposed tensor truncated nuclear norm, which is superior to the traditional tensor nuclear norm. Furthermore, to maintain the structural information, a sparse regularization term, defined in the transform domain, is added into the objective function. Experimental results showed that our proposed algorithm outperforms several state-of-the-art tensor completion schemes.     

A Computational Model for Amodal Completion

This paper presents a computational model to recover the most likely interpretation of the 3D scene structure from a planar image, where some objects may occlude others. The estimated scene interpretation is obtained by integrating some global and local cues and provides both the complete disoccluded objects that form the scene and their ordering according to depth. Our method first computes several distal scenes which are compatible with the proximal planar image. To compute these different hypothesized scenes, we propose a perceptually inspired object disocclusion method, which works by minimizing the Euler’s elastica as well as by incorporating the relatability of partially occluded contours and the convexity of the disoccluded objects. Then, to estimate the preferred scene, we rely on a Bayesian model and define probabilities taking into account the global complexity of the objects in the hypothesized scenes as well as the effort of bringing these objects in their relative position in the planar image, which is also measured by an Euler’s elastica-based quantity. The model is illustrated with numerical experiments on, both, synthetic and real images showing the ability of our model to reconstruct the occluded objects and the preferred perceptual order among them. We also present results on images of the Berkeley dataset with provided figure-ground ground-truth labeling.