多点触控技术在三维虚拟博物馆文物数字可视化中的应用

针对传统博物馆文物数据可视化存在交互效果不佳的问题,提出以陕西省历史博物馆为研究对象,构建一个基于多点触控技术的三维虚拟博物馆设计与漫游系统。首先,采用二维形式进行博物馆三维设计;然后通过多点触控屏幕展示博物馆三维设计效果;最后采用基于变分圆形树图实现层次化数据交互可视化,以提升文物数据空间利用率,并采用层次切换交互技术实现文物数据可视化交互。实验结果表明,对于EOL数据的前6层圆布局测试中,对比于传统的圆形树图和加权能量算法,提出的变分圆形树图的空间利用率提升了4%～52%,且将提出多点触控技术应用到三维虚拟博物馆中可实现文物数据的可视化交互。由此说明,提出的算法可有效提升虚拟博物馆的空间利用率,设计的基于多点触控技术的层次化文物数据可视化交互系统具备一定的可行性。     

在动态演示系统中的图可视化

以图这一典型的数据结构为例,讨论图的圆形布局方案、应用力导引算法的布局方案、应用二维弹性模型算法的布局方案等,讨论这三种布局在图的布局中的应用,对过实验分析它们的优缺点,并总结这三种布局方案在动态演示系统中的可行性.     

交通网络中线圈布局优化的支撑树算法

从图的拓扑特征角度出发, 提出了一种解决交通网络线圈布局优化问题的支撑树算法。新方法首先通过网络超级变换使得流量守恒条件在变换后网络的所有节点上均成立, 再通过分析一般支撑树的拓扑特征, 从而得到一种解决全网观测最小线圈集位置确定问题的图论方法。新方法具有如下特点：a)避免了复杂的数学分析与运算; b)揭示了安装线圈路段的网络拓扑结构; c)利用支撑树多样性的优势, 可提供多种优化布局方案。最后通过算例验证了该方法的合理性与实用性。     

一种查询XML异构数据源的新方法

由于异构数据源存在结构差异和结构不兼容等问题,在其上进行查询是一个挑战.本文根据XML树的特点,对其进行了外延,设计了一种新的XML树的查询方法.通过样式图获得XML树的结点间的语义关系,查询条件可以表示为XML样式图模式,查询不被限定于特定的XML树,给出了基于样式图模式的查询算法.用例说明了该方法如何应用于异构数据源的查询.     

指纹方向图的改进研究

提出一种在现行方向图的基础上改进的圆形方向图,这种圆形方向图过渡平滑、自然、真有很好的连续性、抗噪性,同时对低质量指纹图像具有良好的鲁棒性,能更精确地反应指纹脊线的结构特征,而且计算量比现行方向图减少15%,试验证明了方法的有效性.     

一种正方化有序树图布局算法

针对现有正方化树图有序性差、有序树图正方化性能差的问题,提出一种正方化有序树图布局算法——SOTLA,首先将多个节点捆绑组合构造大权值节点;然后按平均长宽比最接近1和沿最短边方向填充路径限制的原则对节点进行布局;通过对每一组合节点分治并重复上述过程进行布局,最终完成所有单个节点的布局.将该算法应用于50组具有层次结构和数据值大小悬殊特点的农药残留量检测数据中,得到了较好的可视化效果.将该算法与现有的Squarified,Pivot,Strip和Spiral 4种布局算法就平均长宽比、连续性、可读性、稳定性和稳定的平衡性5项评价指标进行对比,实验结果表明,文中算法在连续性和平均长宽比性能上具有明显优势,其可读性、稳定性和稳定的平衡性指标也表现良好.     

求解平衡约束圆形Packing问题的快速启发式并行蚁群算法

带平衡约束圆形Packing问题属于NP-hard问题,求解困难.提出一种求解该问题的快速启发式并行蚁群算法.首先提出一种启发式方法:在轮盘赌选择定序的概率公式中增加质量因子和外围逆时针排列定位待布圆,并用它构造出多样性种群个体(相交圆数不超过3的布局方案).然后将蚁群优化与并行搜索相结合,使种群个体快速收敛到最优解或迭代出存在少量干涉的近似最优解(1～3个相交圆).若为后者,则基于物理模型用最速下降法将其快速调整成最优解.所采用的启发式方法、并行蚁群搜索机制和快速调整策略有机结合提高了算法的搜索精度和效率.数值实验表明该算法在性能指标上优于已存在的算法.     

基于蒙特卡罗树搜索的树图布局

树图是层次数据可视化的常用方法,已有的研究发现,满足逐步加点原则的3种树图布局算法(正方化布局算法、条状布局算法和螺旋线布局算法)在常见的4种优化指标(平均长宽比、稳定性、数据一致性和可读性)上各有优缺点.其中,条状布局算法和螺旋线布局算法的长宽比较大,正方化布局的长宽比仍有优化空间.基于蒙特卡罗树搜索,在树图布局的同时构建对应的搜索树并利用置信度上界公式作为搜索路径的选定标准,在用户可接受时间内对3种布局算法的算术平均长宽比和所提加权平均长宽比分别进行了优化.为了证明算法的有效性,在构造出的3种不同分布、7种不同规模的单层数据集以及真实的多层数据集上测试,并与原算法进行比较分析,最后利用对应结论指导用户选择更好的布局算法以及设置更恰当的参数.     

人工蜂群算法在带约束圆形布局问题中的应用

人工蜂群算法是一种基于蜜蜂采蜜机制的新型演化算法。给出了带平衡约束的圆形布局问题的数学模型,介绍了人工蜂群算法的基本过程以及计算流程,将人工蜂群算法应用于带平衡约束的圆形布局优化中。通过两个实例进行仿真计算,并将计算结果与文献结果比较,验证了人工蜂群算法是解决此类问题的一种有效且实用的群智能算法。     

一种建立控制依赖子图的方法

提出一种基于GCC(GNU Compiler Collection)抽象语法树文本建立控制依赖子图的方法,消除抽象语法树文本中与分析控制流无关的信息,将消除冗余后的抽象语法树文本转化为以邻接表为存储结构的抽象语法树的算法,从而高效地完成了抽象语法树的解析。基于以邻接表为存储结构的抽象语法树建立了控制依赖子图。通过实验证明了该方法的正确性和适用性。     

一种层次结构中多维属性的可视化方法

在很多领域的统计分析中,通常需要分析既具有层次结构又具有多维属性的复杂数据,如食品安全数据、股票数据、网络安全数据等.针对现有多维数据和层次结构的可视化方法不能满足对同时具有层次和多维两种属性数据的可视分析要求,提出了一种树图中的多维坐标MCT(multi-coordinate in treemap)技术.该技术采用基于Squarified和Strip布局算法的树图表示层次结构,用树图中节点矩形的边作为属性轴,通过属性映射、属性点连接、曲线拟合实现层次结构中多维属性的可视化.将该技术应用于全国农药残留侦测数据,实现了对全国各地区、各超市、各农产品中农药残留检出和超标情况的可视化,为领域人员提供了有效的分析工具.MCT技术也可用于其他领域的层次多属性数据的可视化.     

Perceptual guidelines for creating rectangular treemaps

Treemaps are space-filling visualizations that make efficient use of limited display space to depict large amounts of hierarchical data. Creating perceptually effective treemaps requires carefully managing a number of design parameters including the aspect ratio and luminance of rectangles. Moreover, treemaps encode values using area, which has been found to be less accurate than judgments of other visual encodings, such as length. We conduct a series of controlled experiments aimed at producing a set of design guidelines for creating effective rectangular treemaps. We find no evidence that luminance affects area judgments, but observe that aspect ratio does have an effect. Specifically, we find that the accuracy of area comparisons suffers when the compared rectangles have extreme aspect ratios or when both are squares. Contrary to common assumptions, the optimal distribution of rectangle aspect ratios within a treemap should include non-squares, but should avoid extremes. We then compare treemaps with hierarchical bar chart displays to identify the data densities at which length-encoded bar charts become less effective than area-encoded treemaps. We report the transition points at which treemaps exhibit judgment accuracy on par with bar charts for both leaf and non-leaf tree nodes. We also find that even at relatively low data densities treemaps result in faster comparisons than bar charts. Based on these results, we present a set of guidelines for the effective use of treemaps and suggest alternate approaches for treemap layout.     

Browsing zoomable treemaps: structure-aware multi-scale navigation techniques

Treemaps provide an interesting solution for representing hierarchical data. However, most studies have mainly focused on layout algorithms and paid limited attention to the interaction with treemaps. This makes it difficult to explore large data sets and to get access to details, especially to those related to the leaves of the trees. We propose the notion of zoomable treemaps (ZTMs), an hybridization between treemaps and zoomable user interfaces that facilitates the navigation in large hierarchical data sets. By providing a consistent set of interaction techniques, ZTMs make it possible for users to browse through very large data sets (e.g., 700,000 nodes dispatched amongst 13 levels). These techniques use the structure of the displayed data to guide the interaction and provide a way to improve interactive navigation in treemaps.     

Visualizing changes of hierarchical data using treemaps

While the treemap is a popular method for visualizing hierarchical data, it is often difficult for users to track layout and attribute changes when the data evolve over time. When viewing the treemaps side by side or back and forth, there exist several problems that can prevent viewers from performing effective comparisons. Those problems include abrupt layout changes, a lack of prominent visual patterns to represent layouts, and a lack of direct contrast to highlight differences. In this paper, we present strategies to visualize changes of hierarchical data using treemaps. A new treemap layout algorithm is presented to reduce abrupt layout changes and produce consistent visual patterns. Techniques are proposed to effectively visualize the difference and contrast between two treemap snapshots in terms of the map items' colors, sizes, and positions. Experimental data show that our algorithm can achieve a good balance in maintaining a treemap's stability, continuity, readability, and average aspect ratio. A software tool is created to compare treemaps and generate the visualizations. User studies show that the users can better understand the changes in the hierarchy and layout, and more quickly notice the color and size differences using our method.     

正方化树图布局算法研究与优化

层次数据是一种常见的数据类型,它着重表达个体之间的包含和从属关系等。树图是一种非常流行的利用包含关系来表达层次化数据的可视化方法。该方法具有高效的空间利用率及良好的交互性,并广泛应用于各个领域。正方化布局算法是树图可视化方法中常用的算法,但该算法存在无序和稳定性差等不足。提出了一种优化算法来改进该算法的不足,并通过实验数据证明了优化后算法的有效性。     

Stacking graphic elements to avoid over-plotting

An ongoing challenge for information visualization is how to deal with over-plotting forced by ties or the relatively limited visual field of display devices. A popular solution is to represent local data density with area (bubble plots, treemaps), color (heatmaps), or aggregation (histograms, kernel densities, pixel displays). All of these methods have at least one of three deficiencies:1) magnitude judgments are biased because area and color have convex downward perceptual functions, 2) area, hue, and brightness have relatively restricted ranges of perceptual intensity compared to length representations, and/or 3) it is difficult to brush or link to individual cases when viewing aggregations. In this paper, we introduce a new technique for visualizing and interacting with datasets that preserves density information by stacking overlapping cases. The overlapping data can be points or lines or other geometric elements, depending on the type of plot. We show real-dataset applications of this stacking paradigm and compare them to other techniques that deal with over-plotting in high-dimensional displays.     

Treemaps for workload visualization

The author uses treemaps to present the state of work in a grid or other distributed computing environments, providing users with a view of overall performance and allowing performance analysts to explore data in a creative manner.     

Quantitative Comparison of Time-Dependent Treemaps

Rectangular treemaps are often the method of choice to visualize large hierarchical datasets. Nowadays such datasets are available over time, hence there is a need for (a) treemaps that can handle time-dependent data, and (b) corresponding quality criteria that cover both a treemap's visual quality and its stability over time. In recent years a wide variety of (stable) treemapping algorithms has been proposed, with various advantages and limitations. We aim to provide insights to researchers and practitioners to allow them to make an informed choice when selecting a treemapping algorithm for specific applications and data. To this end, we perform an extensive quantitative evaluation of rectangular treemaps for time-dependent data. As part of this evaluation we propose a novel classification scheme for time-dependent datasets. Specifically, we observe that the performance of treemapping algorithms depends on the characteristics of the datasets used. We identify four potential representative features that characterize time-dependent hierarchical datasets and classify all datasets used in our experiments accordingly. We experimentally test the validity of this classification on more than 2000 datasets, and analyze the relative performance of 14 state-of-the-art rectangular treemapping algorithms across varying features. Finally, we visually summarize our results with respect to both visual quality and stability to aid users in making an informed choice among treemapping algorithms. All datasets, metrics, and algorithms are openly available to facilitate reuse and further comparative studies.     

一种新的图像圆环点坐标求解方法*

提出了一种求解等边三角形及其内切圆的图像圆环点坐标新方法.通过提取模板图像的角点,利用高等几何中的拉盖尔定理及其推论来计算其图像圆环点坐标,实验数据证实了该方法的有效性.利用该方法求得的坐标值可以用于摄像机的标定等领域.     

Visual analysis of the air pollution problem in Hong Kong

We present a comprehensive system for weather data visualization. Weather data are multivariate and contain vector fields formed by wind speed and direction. Several well-established visualization techniques such as parallel coordinates and polar systems are integrated into our system. We also develop various novel methods, including circular pixel bar charts embedded into polar systems, enhanced parallel coordinates with S-shape axis, and weighted complete graphs. Our system was used to analyze the air pollution problem in Hong Kong and some interesting patterns have been found.