Semi‐Regular Triangle Remeshing: A Comprehensive Study

Semi‐regular triangle remeshing algorithms convert irregular surface meshes into semi‐regular ones. Especially in the field of computer graphics, semi‐regularity is an interesting property because it makes meshes highly suitable for multi‐resolution analysis. In this paper, we survey the numerous remeshing algorithms that have been developed over the past two decades. We propose different classifications to give new and comprehensible insights into both existing methods and issues. We describe how considerable obstacles have already been overcome, and discuss promising perspectives.     

Computing Minimum Area Homologies

Calculating and categorizing the similarity of curves is a fundamental problem which has generated much recent interest. However, to date there are no implementations of these algorithms for curves on surfaces with provable guarantees on the quality of the measure. In this paper, we present a similarity measure for any two cycles that are homologous, where we calculate the minimum area of any homology (or connected bounding chain) between the two cycles. The minimum area homology exists for broader classes of cycles than previous measures which are based on homotopy. It is also much easier to compute than previously defined measures, yielding an efficient implementation that is based on linear algebra tools. We demonstrate our algorithm on a range of inputs, showing examples which highlight the feasibility of this similarity measure.     

A sliding window technique for interactive high-performance computing scenarios

Interactive high-performance computing is doubtlessly beneficial for many computational science and engineering applications whenever simulation results should be visually processed in real time, i.e. during the computation process. Nevertheless, interactive HPC entails a lot of new challenges that have to be solved – one of them addressing the fast and efficient data transfer between a simulation back end and visualisation front end, as several gigabytes of data per second are nothing unusual for a simulation running on some (hundred) thousand cores. Here, a new approach based on a sliding window technique is introduced that copes with any bandwidth limitations and allows users to study both large and small scale effects of the simulation results in an interactive fashion.     

投票理论研究现状及其展望

社会选择理论是研究如何表达和聚合个体选择的一门学问.而社会选择理论与计算机科学的融合产生了称为计算社会选择的交叉学科,该学科成为社会计算的重要研究内容之一,在人工智能、经济和计算性理论领域引起了轰动.其一方面引入了复杂性分析和算法设计等计算机学科中常用的技术来对社会选择机制进行研究;另一方面也通过引入社会选择理论中的概念来推动计算机技术的发展,特别是在多智能体系统研究中有着成功的应用.投票理论是计算社会选择中最重要的研究主题之一.首先介绍常见的投票方法以及投票理论的形式化框架;再对投票理论中所关心的操纵问题做分析;然后介绍在组合域上的投票;最后对其他相关问题作简要介绍,并对该领域未来的发展与应用做出展望.     

Designing Camera Networks by Convex Quadratic Programming

In this paper, we study the problem of automatic camera placement for computer graphics and computer vision applications. We extend the problem formulations of previous work by proposing a novel way to incorporate visibility constraints and camera‐to‐camera relationships. For example, the placement solution can be encouraged to have cameras that image the same important locations from different viewing directions, which can enable reconstruction and surveillance tasks to perform better. We show that the general camera placement problem can be formulated mathematically as a convex binary quadratic program (BQP) under linear constraints. Moreover, we propose an optimization strategy with a favorable trade‐off between speed and solution quality. Our solution is almost as fast as a greedy treatment of the problem, but the quality is significantly higher, so much so that it is comparable to exact solutions that take orders of magnitude more computation time. Because it is computationally attractive, our method also allows users to explore the space of solutions for variations in input parameters. To evaluate its effectiveness, we show a range of 3D results on real‐world floorplans (garage, hotel, mall, and airport).     

Terrain Modelling from Feature Primitives

We introduce a compact hierarchical procedural model that combines feature‐based primitives to describe complex terrains with varying level of detail. Our model is inspired by skeletal implicit surfaces and defines the terrain elevation function by using a construction tree. Leaves represent terrain features and they are generic parametrized skeletal primitives, such as mountains, ridges, valleys, rivers, lakes or roads. Inner nodes combine the leaves and subtrees by carving, blending or warping operators. The elevation of the terrain at a given point is evaluated by traversing the tree and by combining the contributions of the primitives. The definition of the tree leaves and operators guarantees that the resulting elevation function is Lipschitz, which speeds up the sphere tracing used to render the terrain. Our model is compact and allows for the creation of large terrains with a high level o detail using a reduced set of primitives. We show the creation of different kinds of landscapes and demonstrate that our model allows to efficiently control the shape and distribution of landform features.     

Woodification: User‐Controlled Cambial Growth Modeling

We present a botanical simulation of secondary (cambial) tree growth coupled to a physical cracking simulation of its bark. Whereas level set growth would use a fixed resolution voxel grid, our system extends the deformable simplicial complex (DSC), supporting new biological growth functions robustly on any surface polygonal mesh with adaptive subdivision, collision detection and topological control. We extend the DSC with temporally coherent texturing, and surface cracking with a user‐controllable biological model coupled to the stresses introduced by the cambial growth model.     

Performance comparison of reduced models for leak detection in water distribution networks

This paper presents a methodology for comparing the performance of model-reduction strategies to be used with a diagnostic methodology for leak detection in water distribution networks. The goal is to find reduction strategies that are suitable for error-domain model falsification, a model based data interpretation methodology. Twelve reduction strategies are derived from five strategy categories. Categories differ according to the manner in which nodes are selected for deletion. A node is selected for deletion according to: (1) the diameter of the pipes; (2) the number of pipes linked to a node; (3) the angle of the pipes in the case of two-pipe nodes; (4) the distribution of the water demand; and, (5) a pair-wise combination of some categories.The methodology is illustrated using part of a real network. Performance is evaluated first by judging the equivalency of the reduced network with the initial network (before the application of any reduction procedure) and secondly, by assessing the compatibility with the diagnostic methodology. The results show that for each reduction strategy the equivalency of networks is verified. Computational time can be reduced to less than 20% of the non-reduced network in the best case. Results of diagnostic performance show that the performance decreases when using reduced networks. The reduction strategy with the best diagnostic performance is that based on the angle of two-pipe nodes, with an angle threshold of 165°. In addition, the sensitivity of the performance of the reduced networks to variation in leak intensity is evaluated. Results show that the reduction strategies where the number of nodes is significantly reduced are the most sensitive.Finally this paper describes a Pareto analysis that is used to select the reduction strategy that is a good compromise between reduction of computational time and performance of the diagnosis. In this context, the extension strategy is the most attractive.     

A computational software tool for the minimization of costs and greenhouse gas emissions associated with water distribution systems

While evolutionary algorithms have been applied extensively to water resource problems, there remains a need to unify and consolidate computational and software approaches to solving these problems. In order to facilitate this for the minimization of costs and greenhouse gas emissions of water distribution systems, the water distribution cost-emissions nexus (WCEN) computational software framework is introduced in this paper. The software is freely available and can be easily modified in order to facilitate consistency of modeling, simulation and evaluation within different research studies. In addition, it enables consideration of the time-dependent variation of operational choices, such as emissions factors, electricity tariffs and water demands, which has not been done previously. The utility of the framework is demonstrated for a case study, the results of which show that consideration of such variations can significantly affect optimal design and operational decisions, as well as their costs and GHG emissions.