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2011 IEEE Pacific Visualization Symposium最新文献

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Keynote address: Why everyone seems to be using spring embedders for network visualization, and should not 主题演讲:为什么每个人似乎都在使用spring嵌入器来实现网络可视化,而不应该这样做
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742366
U. Brandes
The main algorithmic challenge in network visualization is the placement of nodes. While plenty of layout algorithms have been proposed, the vast majority of information visualization tools appears to utilize (sometimes a variant of) one of two algorithms: the approach of Fruchterman and Reingold or that of Kamada and Kawai. Both are often referred to as force-directed methods, or spring embedders, and praised for their general applicability, high adaptability, and simplicity. I will argue that commonly used implementations and even the approaches themselves are outdated and, in fact, have always been. They should be replaced by variants of multidimensional scaling that display superior results and scalability, and are just as flexible and easy to implement. Some of these statements may actually be backed by evidence.
网络可视化的主要算法挑战是节点的放置。虽然已经提出了大量的布局算法,但绝大多数信息可视化工具似乎利用(有时是一种变体)以下两种算法之一:Fruchterman和Reingold的方法或Kamada和Kawai的方法。这两种方法通常被称为定向力方法或弹簧嵌入器,并因其普遍适用性、高适应性和简单性而受到称赞。我认为常用的实现甚至方法本身都是过时的,事实上,一直都是。它们应该被多维缩放的变体所取代,这些变体可以显示更好的结果和可伸缩性,并且同样灵活且易于实现。其中一些说法实际上是有证据支持的。
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引用次数: 3
Dynamic network visualization in 1.5D 1.5D动态网络可视化
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742388
Lei Shi, Chen Wang, Zhen Wen
The dynamic network visualization has been a challenging topic due to the complexity introduced by the extra time dimension. Existing solutions to this problem are usually good for the overview and presentation, but not for the interactive analysis. We propose in this paper a new approach which only considers the dynamic network central to a focus node (aka dynamic ego network). The navigation of the entire network is achieved by switching the focus node with user interactions. With this approach, the complexity of the compressed dynamic network is greatly reduced without sacrificing the network and time affinity central to the focus node. As a result, we are able to present each dynamic ego network in a single static view, well supporting user analysis on temporal network patterns. We describe our general framework including the network data pre-processing, 1.5D network and trend visualization design, layout algorithms, as well as several customized interactions. In addition, we show that our approach can also be extended to visualize the event-based and multimodal dynamic networks. Finally, we demonstrate, through two practical case studies, the effectiveness of our solution in support of visual evidence and pattern discovery.
由于额外的时间维度带来的复杂性,动态网络可视化一直是一个具有挑战性的课题。这个问题的现有解决方案通常适合于概述和表示,但不适合交互式分析。本文提出了一种仅考虑以焦点节点为中心的动态网络(即动态自我网络)的新方法。整个网络的导航是通过用户交互切换焦点节点来实现的。这种方法在不牺牲焦点节点中心的网络和时间亲和性的前提下,大大降低了压缩动态网络的复杂性。因此,我们能够在单个静态视图中呈现每个动态自我网络,很好地支持对时间网络模式的用户分析。我们描述了我们的总体框架,包括网络数据预处理,1.5D网络和趋势可视化设计,布局算法,以及一些定制的交互。此外,我们表明,我们的方法也可以扩展到可视化基于事件和多模态的动态网络。最后,我们通过两个实际案例研究证明了我们的解决方案在支持视觉证据和模式发现方面的有效性。
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引用次数: 42
The NETSPEAK WORDGRAPH: Visualizing keywords in context NETSPEAK WORDGRAPH:可视化上下文中的关键字
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742381
P. Riehmann, Henning Gruendl, B. Fröhlich, Martin Potthast, Martin Trenkmann, Benno Stein
NETSPEAK helps writers in choosing words while writing a text. It checks for the commonness of phrases and allows for the retrieval of alternatives by means of wildcard queries. To support such queries, we implement a scalable retrieval engine, which returns high-quality results within milliseconds using a probabilistic retrieval strategy. The results are displayed as WORDGRAPH visualization or as a textual list. The graphical interface provides an effective means for interactive exploration of search results using filter techniques, query expansion and navigation. Our observations indicate that, of three investigated retrieval tasks, the textual interface is sufficient for the phrase verification task, wherein both views support context-sensitive word choice, and the WORDGRAPH best supports the exploration of a phrase's context or the underlying corpus. The preferred view for context-sensitive word choice seems to depend on query complexity (i.e. the number of wildcards in a query).
NETSPEAK帮助作家在写作时选词。它检查短语的共性,并允许通过通配符查询检索备选项。为了支持这样的查询,我们实现了一个可伸缩的检索引擎,它使用概率检索策略在几毫秒内返回高质量的结果。结果显示为WORDGRAPH可视化或文本列表。图形界面为使用过滤技术、查询扩展和导航对搜索结果进行交互式探索提供了有效的手段。我们的观察表明,在三个被调查的检索任务中,文本界面足以满足短语验证任务,其中两个视图都支持上下文敏感的单词选择,WORDGRAPH最好地支持短语上下文或底层语料库的探索。上下文敏感的单词选择的首选视图似乎取决于查询的复杂性(即查询中的通配符数量)。
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引用次数: 10
View point evaluation and streamline filtering for flow visualization 视点评估和流线过滤流可视化
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742376
Teng-Yok Lee, O. Mishchenko, Han-Wei Shen, R. Crawfis
Visualization of flow fields with geometric primitives is often challenging due to occlusion that is inevitably introduced by 3D streamlines. In this paper, we present a novel view-dependent algorithm that can minimize occlusion and reveal important flow features for three dimensional flow fields. To analyze regions of higher importance, we utilize Shannon's entropy as a measure of vector complexity. An entropy field in the form of a three dimensional volume is extracted from the input vector field. To utilize this view-independent complexity measure for view-dependent calculations, we introduce the notion of a maximal entropy projection (MEP) framebuffer, which stores maximal entropy values as well as the corresponding depth values for a given viewpoint. With this information, we develop a view-dependent streamline selection algorithm that can evaluate and choose streamlines that will cause minimum occlusion to regions of higher importance. Based on a similar concept, we also propose a viewpoint selection algorithm that works hand-in-hand with our streamline selection algorithm to maximize the visibility of high complexity regions in the flow field.
由于三维流线不可避免地引入遮挡,使用几何基元的流场可视化通常具有挑战性。在本文中,我们提出了一种新的视图依赖算法,该算法可以最小化遮挡并揭示三维流场的重要流动特征。为了分析更重要的区域,我们利用香农熵作为向量复杂度的度量。从输入向量场中提取出三维体积形式的熵场。为了利用这种与视图无关的复杂性度量来进行与视图相关的计算,我们引入了最大熵投影(MEP)帧缓冲区的概念,它存储了给定视点的最大熵值以及相应的深度值。利用这些信息,我们开发了一种依赖于视图的流线选择算法,该算法可以评估和选择对更重要的区域造成最小遮挡的流线。基于类似的概念,我们还提出了一种视点选择算法,该算法与我们的流线选择算法携手工作,以最大限度地提高流场中高复杂性区域的可见性。
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引用次数: 73
Analyzing information transfer in time-varying multivariate data 时变多元数据中的信息传递分析
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742378
Chaoli Wang, Hongfeng Yu, R. Grout, K. Ma, Jacqueline H. Chen
Effective analysis and visualization of time-varying multivariate data is crucial for understanding complex and dynamic variable interaction and temporal evolution. Advances made in this area are mainly on query-driven visualization and correlation exploration. Solutions and techniques that investigate the important aspect of causal relationships among variables have not been sought. In this paper, we present a new approach to analyzing and visualizing time-varying multivariate volumetric and particle data sets through the study of information flow using the information-theoretic concept of transfer entropy. We employ time plot and circular graph to show information transfer for an overview of relations among all pairs of variables. To intuitively illustrate the influence relation between a pair of variables in the visualization, we modulate the color saturation and opacity for volumetric data sets and present three different visual representations, namely, ellipse, smoke, and metaball, for particle data sets. We demonstrate this information-theoretic approach and present our findings with three time-varying multivariate data sets produced from scientific simulations.
时变多变量数据的有效分析和可视化对于理解复杂的动态变量相互作用和时间演化至关重要。该领域的进展主要集中在查询驱动的可视化和相关性探索方面。研究变量之间因果关系的重要方面的解决方案和技术尚未得到寻求。本文利用传递熵的信息理论概念,通过信息流的研究,提出了一种分析和可视化时变多变量体积和粒子数据集的新方法。我们使用时间图和圆形图来表示信息传递,以概述所有变量对之间的关系。为了直观地说明可视化中一对变量之间的影响关系,我们调整了体积数据集的颜色饱和度和不透明度,并为粒子数据集提供了三种不同的视觉表示,即椭圆、烟雾和元球。我们展示了这种信息理论方法,并通过科学模拟产生的三个时变多元数据集展示了我们的发现。
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引用次数: 41
Interactive seismic interpretation with piecewise global energy minimization 分段全球能量最小化的交互式地震解释
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742373
T. Höllt, J. Beyer, Fritz Gschwantner, P. Muigg, H. Doleisch, G. Heinemann, M. Hadwiger
Increasing demands in world-wide energy consumption and oil depletion of large reservoirs have resulted in the need for exploring smaller and more complex oil reservoirs. Planning of the reservoir valorization usually starts with creating a model of the subsurface structures, including seismic faults and horizons. However, seismic interpretation and horizon tracing is a difficult and error-prone task, often resulting in hours of work needing to be manually repeated. In this paper, we propose a novel, interactive workflow for horizon interpretation based on well positions, which include additional geological and geophysical data captured by actual drillings. Instead of interpreting the volume slice-by-slice in 2D, we propose 3D seismic interpretation based on well positions. We introduce a combination of 2D and 3D minimal cost path and minimal cost surface tracing for extracting horizons with very little user input. By processing the volume based on well positions rather than slice-based, we are able to create a piecewise optimal horizon surface at interactive rates. We have integrated our system into a visual analysis platform which supports multiple linked views for fast verification, exploration and analysis of the extracted horizons. The system is currently being evaluated by our collaborating domain experts.
世界范围内能源消费需求的增加和大型油藏的石油枯竭导致需要勘探更小和更复杂的油藏。油藏价值评估的规划通常从建立地下结构模型开始,包括地震断层和层位。然而,地震解释和层位追踪是一项困难且容易出错的任务,通常需要花费数小时的人工重复工作。在本文中,我们提出了一种基于井位的新的交互式层位解释工作流程,其中包括实际钻井捕获的额外地质和地球物理数据。我们提出了基于井位的三维地震解释方法,而不是以二维方式逐层解释体积。我们引入了2D和3D最小成本路径和最小成本表面跟踪的组合,用于在用户输入很少的情况下提取地平线。通过基于井位而不是基于切片来处理体积,我们能够以交互速率创建分段最佳水平面。我们已经将我们的系统集成到一个可视化分析平台中,该平台支持多个链接视图,用于快速验证、勘探和分析提取的视界。该系统目前正在由我们合作的领域专家进行评估。
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引用次数: 28
TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection TripVista:三视角视觉轨迹分析及其在十字路口微观交通数据上的应用
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742386
Hanqi Guo, Zuchao Wang, Bowen Yu, Huijing Zhao, Xiaoru Yuan
In this paper, we present an interactive visual analytics system, Triple Perspective Visual Trajectory Analytics (TripVista), for exploring and analyzing complex traffic trajectory data. The users are equipped with a carefully designed interface to inspect data interactively from three perspectives (spatial, temporal and multi-dimensional views). While most previous works, in both visualization and transportation research, focused on the macro aspects of traffic flows, we develop visualization methods to investigate and analyze microscopic traffic patterns and abnormal behaviors. In the spatial view of our system, traffic trajectories with various presentation styles are directly interactive with user brushing, together with convenient pattern exploration and selection through ring-style sliders. Improved ThemeRiver, embedded with glyphs indicating directional information, and multiple scatterplots with time as horizontal axes illustrate temporal information of the traffic flows. Our system also harnesses the power of parallel coordinates to visualize the multi-dimensional aspects of the traffic trajectory data. The above three view components are linked closely and interactively to provide access to multiple perspectives for users. Experiments show that our system is capable of effectively finding both regular and abnormal traffic flow patterns.
在本文中,我们提出了一个交互式视觉分析系统,Triple Perspective visual Trajectory analytics (TripVista),用于探索和分析复杂的交通轨迹数据。用户配备了精心设计的界面,可以从三个角度(空间、时间和多维视图)交互式地查看数据。在可视化和交通研究方面,以往的大部分工作都集中在交通流的宏观方面,而我们开发了可视化方法来调查和分析微观交通模式和异常行为。在我们的系统的空间视图中,各种呈现风格的交通轨迹与用户刷屏直接交互,并通过环形滑块方便地进行模式探索和选择。改进的ThemeRiver,嵌入了指示方向信息的符号,以及以时间为水平轴的多个散点图,说明交通流的时间信息。我们的系统还利用平行坐标的力量来可视化交通轨迹数据的多维方面。上述三个视图组件紧密地交互连接在一起,为用户提供对多个透视图的访问。实验表明,该系统能够有效地发现正常和异常的交通流模式。
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引用次数: 215
Multilevel agglomerative edge bundling for visualizing large graphs 用于可视化大型图形的多级聚集边缘捆绑
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742389
E. Gansner, Yifan Hu, S. North, C. Scheidegger
Graphs are often used to encapsulate relationships between objects. Node-link diagrams, commonly used to visualize graphs, suffer from visual clutter on large graphs. Edge bundling is an effective technique for alleviating clutter and revealing high-level edge patterns. Previous methods for general graph layouts either require a control mesh to guide the bundling process, which can introduce high variation in curvature along the bundles, or all-to-all force and compatibility calculations, which is not scalable. We propose a multilevel agglomerative edge bundling method based on a principled approach of minimizing ink needed to represent edges, with additional constraints on the curvature of the resulting splines. The proposed method is much faster than previous ones, able to bundle hundreds of thousands of edges in seconds, and one million edges in a few minutes.
图通常用于封装对象之间的关系。节点链接图通常用于可视化图形,但在大型图形中会出现视觉混乱。边缘捆绑是一种有效的技术,可以减轻混乱,揭示高级边缘模式。以前用于一般图形布局的方法要么需要一个控制网格来指导捆绑过程,这可能会导致捆绑过程中曲率的高度变化,要么需要全对全的力和兼容性计算,这是不可扩展的。我们提出了一种基于最小化表示边缘所需墨水的原则方法的多级凝聚边缘捆绑方法,并对所产生的样条的曲率进行了额外的约束。该方法比以前的方法快得多,可以在几秒钟内捆绑数十万条边,并在几分钟内捆绑100万条边。
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引用次数: 181
Context-aware volume navigation 上下文感知的卷导航
Pub Date : 2011-03-01 DOI: 10.1109/PACIFICVIS.2011.5742367
Stefan Diepenbrock, T. Ropinski, K. Hinrichs
The trackball metaphor is exploited in many applications where volumetric data needs to be explored. Although it provides an intuitive way to inspect the overall structure of objects of interest, an in-detail inspection can be tedious - or when cavities occur even impossible. Therefore we propose a context-aware navigation technique for the exploration of volumetric data. While navigation techniques for polygonal data require information about the rendered geometry, this strategy is not sufficient in the area of volume rendering. Since rendering parameters, e.g., the transfer function, have a strong influence on the visualized structures, they also affect the features to be explored. To compensate for this effect we propose a novel image-based navigation approach for volumetric data. While being intuitive to use, the proposed technique allows the user to perform complex navigation tasks, in particular to get an overview as well as to perform an in-detail inspection without any navigation mode switches. The technique can be easily integrated into raycasting based volume renderers, needs no extra data structures and is independent of the data set as well as the rendering parameters. We will discuss the underlying concepts, explain how to enable the navigation at interactive frame rates using OpenCL, and evaluate its usability as well as its performance.
轨迹球比喻在许多需要探索体积数据的应用程序中得到了利用。虽然它提供了一种直观的方法来检查感兴趣的对象的整体结构,但详细检查可能是乏味的-或者当发生蛀牙时甚至不可能。因此,我们提出了一种用于体积数据探索的上下文感知导航技术。虽然针对多边形数据的导航技术需要关于渲染几何的信息,但这种策略在体绘制领域是不够的。由于渲染参数(例如传递函数)对可视化结构有很强的影响,因此它们也会影响待探索的特征。为了弥补这种影响,我们提出了一种新的基于图像的体积数据导航方法。虽然使用起来很直观,但所提出的技术允许用户执行复杂的导航任务,特别是在没有任何导航模式切换的情况下获得概述以及执行详细检查。该技术可以很容易地集成到基于光线投射的体渲染器中,不需要额外的数据结构,并且独立于数据集和渲染参数。我们将讨论底层概念,解释如何使用OpenCL在交互帧率下启用导航,并评估其可用性和性能。
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引用次数: 8
IEEE Visualization and Graphics Technical Committee (VGTC) IEEE可视化与图形技术委员会(VGTC)
Pub Date : 2004-10-10 DOI: 10.1109/visual.2004.44
A. Varshney, R. Brady, Bowen Loftin, G. Nielson, Hanspeter Pfister, W. Ribarsky, R. Moorhead, L. Rosenblum, L. Auvil, Torsten Möller, M. Haley, S. Julier, Lisa Avila, Steve Lamont, D. Ebert, K. Gaither, E. Gröller, M. Livingston, J. Stasko
The IEEE Visualization and Graphics Technical Committee (VGTC) is a formal subcommittee of the Technical Activities Board (TAB) of the IEEE Computer Society. The VGTC provides technical leadership and organizes technical activities in the areas of visualization, computer graphics, virtual and augmented reality, and interaction.
IEEE可视化和图形技术委员会(VGTC)是IEEE计算机协会技术活动委员会(TAB)的正式小组委员会。VGTC在可视化、计算机图形学、虚拟和增强现实以及交互等领域提供技术领导和组织技术活动。
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引用次数: 0
期刊
2011 IEEE Pacific Visualization Symposium
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