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Splatting the Lines in parallel Coordinates

COMPUTER graphics FORUM 2009年第3期28卷 759-766页

作者： Zhou, Hong Cui, Weiwei Qu, Huamin Wu, Yingcai Yuan, Xiaoru Zhuo, Wei Hong Kong Univ Sci & Technol Hong Kong Hong Kong Peoples R China Peking Univ Sch EECS Beijing Peoples R China Peking Univ Key Lab Machine Percept Minist Educ Beijing Peoples R China

In this paper, we propose a novel splatting framework for clutter reduction and pattern revealing in parallel coordinates. Our framework consists of two major components: a polyline splatter for cluster detection and a segment splatter for clutter reduction. The cluster detection is performed by splatting the lines one by one into the parallel coordinates plots, and for each splatted line we enhance its neighboring lines and suppress irrelevant ones. To reduce visual clutter caused by line crossings and overlappings in the clustered results, we provide a segment splatter which represents each polyline by one segment and splats these segments with different speeds, colors, and lengths from the leftmost axis to the rightmost axis. Users can interactively control both the polyline splatting and the segment splatting processes to emphasize the features they are interested in. The experimental results demonstrate that our framework can effectively reveal some hidden patterns in parallel coordinates.

关键词： HYPERSPACE ALGORITHMS DIGITAL images ANIMATION (Cinematography) ELECTRONIC data processing DOCUMENT clustering

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parallel Adaptive Simplification of Massive Meshes

Parallel Adaptive Simplification of Massive Meshes

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11th International Conference on Computer-Aided Design and Computer graphics

作者： Li Nan Gao Pengdong Lu Yongquan Qiu Chu Wang Jintao Yu Wenhua Commun Univ China Ctr High Performance Comp Beijing 100024 Peoples R China

ISBN: (纸本)9781424437009

A parallel simplification method based on vertex clustering for out-of-core meshes is presented in this paper. To reduce file I/O, only one linear scan is performed in this method to partition the original model into equal batches. Then vertex normal vectors and coefficients of each triangle plane are calculated with some inter-task communications. The portion assigned to each processor is simplified by an improved vertex clustering method. Finally, all reduced data are sent back to the master node and assembled into the simplified mesh. The partition stitching is fulfilled simply by using a global vertex. index. A lot of experiments have demonstrated that the proposed method can handle extremely large data set and speed up the execution time obviously as well as produce approximations with high quality.

关键词： Partitioning algorithms Master-slave Clustering methods High performance computing Vectors Assembly Solid modeling Application software data visualization Computer graphics

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How interactive visualization can assist investigative analysis: Views and perspectives from domain experts

How interactive visualization can assist investigative analy...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Stasko, John Cohen, Sarah Hunter, Lawrence Parry, Joe Georgia Tech. United States Duke University United States Univ. of Colorado School of Medicine United States i2 Limited United Kingdom

ISBN: (纸本)9781424452835

Interactive visualization could become an essential tool in the work of investigative analysts. visualization could help analysts to explore large collections of data and documents, supporting the analysts' investigative sense-making processes. This panel gathers recognized leaders from three important domains, investigative reporting, biosciences (genomics), and intelligence analysis, that all include a fundamental investigative analysis component. The panelists will provide a glimpse into their worlds, describing and illustrating the data they examine, the goals and methods of their analysts, and the culture of their respective professions. In particular, the panelists will explore how visualization could potentially benefit investigators from their domain and they will provide guidance for visualization researchers seeking to collaborate with their colleagues. ©2009 ieee.

关键词： Genome

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Model space visualization for multivariate linear trend discovery

Model space visualization for multivariate linear trend disc...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Guo, Zhenyu Ward, Matthew O. Rundensteiner, Elke A. Computer Science Department Worcester Polytechnic Institute United States

ISBN: (纸本)9781424452835

Discovering and extracting linear trends and correlations in datasets is very important for analysts to understand multivariate phenomena. However, current widely used multivariate visualization techniques, such as parallel coordinates and scatterplot matrices, fail to reveal and illustrate such linear relationships intuitively, especially when more than 3 variables are involved or multiple trends coexist in the dataset. We present a novel multivariate model parameter space visualization system that helps analysts discover single and multiple linear patterns and extract subsets of data that fit a model well. Using this system, analysts are able to explore and navigate in model parameter space, interactively select and tune patterns, and refine the model for accuracy using computational techniques. We build connections between model space and data space visually, allowing analysts to employ their domain knowledge during exploration to better interpret the patterns they discover and their validity. Case studies with real datasets are used to investigate the effectiveness of the visualizations. ©2009 ieee.

关键词： visualization

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ProcessLine: Visualizing time-series data in process industry

ProcessLine: Visualizing time-series data in process industr...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Xiongfei, Luo Hongan, Wang Feng, Tian Wei, Liu Dongxing, Teng Guozhong, Dai Graduate University Chinese Academy of Sciences Beijing China Institute of Software Chinese Academy of Sciences Beijing China State Key Lab. of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424452835

In modern process industry, it is often difficult to analyze a manufacture process due to its numerous time-series data. Analysts wish to not only interpret the evolution of data over time in a working procedure, but also examine the changes in the whole production process through time. To meet such analytic requirements, we have developed ProcessLine, an interactive visualization tool for a large amount of time-series data in process industry. The data are displayed in a fisheye timeline. ProcessLine provides good overviews for the whole production process and details for the focused working procedure. A preliminary user study using beer industry production data has shown that the tool is effective. ©2009 ieee.

关键词： visualization

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A scalable architecture for visual data exploration

A scalable architecture for visual data exploration

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Decker, Jonathan Godwin, Alex Livingston, Mark A. Royle, Denise Naval Research Laboratory United States Charles River Analytics United States

ISBN: (纸本)9781424452835

Intelligence analysts in the areas of defense and homeland security are now faced with the difficult problem of discerning the relevant details amidst massive data stores. We propose a component-based visualization architecture that is built specifically to encourage the flexible exploration of geospatial event databases. The proposed system is designed to deploy on a variety of display layouts, from a single laptop screen to a multi-monitor tiled-display. By utilizing a combination of parallel coordinates, principal components plots, and other data views, analysts may reduce the dimensionality of a data set to its most salient features. Of particular value to our target applications are understanding correlations between data layers, both within a single view and across multiple views. Our proposed system aims to address the limited scalability associated with coordinated multiple views (CMVs) through the implementation of an efficient core application which is extensible by the end-user. ©2009 ieee.

关键词： visualization

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Time and Streak Surfaces for Flow visualization in large Time-Varying data Sets

Time and Streak Surfaces for Flow Visualization in Large Tim...

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ieee Information visualization Conference/ieee visualization Conference

作者： Krishnan, Hari Garth, Christoph Joy, Kenneth I. Univ Calif Davis Inst Data Anal & Visualizat Davis CA 95616 USA

Time and streak surfaces are ideal tools to illustrate time-varying vector fields since they directly appeal to the intuition about coherently moving particles. However, efficient generation of high-quality time and streak surfaces for complex, large and time-varying vector field data has been elusive due to the computational effort involved. In this work, we propose a novel algorithm for computing such surfaces. Our approach is based on a decoupling of surface advection and surface adaptation and yields improved efficiency over other surface tracking methods, and allows us to leverage inherent parallelization opportunities in the surface advection, resulting in more rapid parallel computation. Moreover, we obtain as a result of our algorithm the entire evolution of a time or streak surface in a compact representation, allowing for interactive, high-quality rendering, visualization and exploration of the evolving surface. Finally, we discuss a number of ways to improve surface depiction through advanced rendering and texturing, while preserving interactivity, and provide a number of examples for real-world datasets and analyze the behavior of our algorithm on them.

关键词： 3D vector field visualization flow visualization time-varying time and streak surfaces surface extraction

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ieee Pacific visualization symposium, PacificVis 2009 - Proceedings

IEEE Pacific Visualization Symposium, PacificVis 2009 - Proc...

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ieee Pacific visualization symposium, PacificVis 2009

ISBN: (纸本)9781424444045

The proceedings contain 26 papers. The topics discussed include: capstone address: introduction to processing and visualization of chang'e-1 Lunar exploration data;visualizing time-varying features with TAC-based distance fields;interactive feature extraction and tracking by utilizing region coherency;an organization topographic map for visualizing business hierarchical relationships;visualizing metrics on areas of interest in software architecture diagrams;toward effective insight management in visual analytics systems;optimized data transfer for time-dependent, GPU-based glyphs;out-of-core volume rendering for time-varying fields using a space-partitioning time (SPT) tree;point-based tree representation: a new approach for large hierarchies;and a self-adaptive treemap-based technique for visualizing hierarchical data in 3D.

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A framework for uncertainty-aware visual analytics

A framework for uncertainty-aware visual analytics

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Correa, Carlos D. Chan, Yu-Hsuan Kwan-Liu, Ma University of California Davis CA United States

ISBN: (纸本)9781424452835

Visual analytics has become an important tool for gaining insight on large and complex collections of data. Numerous statistical tools and data transformations, such as projections, binning and clustering, have been coupled with visualization to help analysts understand data better and faster. However, data is inherently uncertain, due to error, noise or unreliable sources. When making decisions based on uncertain data, it is important to quantify and present to the analyst both the aggregated uncertainty of the results and the impact of the sources of that uncertainty. In this paper, we present a new framework to support uncertainty in the visual analytics process, through statistic methods such as uncertainty modeling, propagation and aggregation. We show that data transformations, such as regression, principal component analysis and k-means clustering, can be adapted to account for uncertainty. This framework leads to better visualizations that improve the decision-making process and help analysts gain insight on the analytic process itself. ©2009 ieee.

关键词： visualization

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Combining automated analysis and visualization techniques for effective exploration of high-dimensional data

Combining automated analysis and visualization techniques fo...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Tatu, Andrada Albuquerque, Georgia Eisemann, Martin Schneidewind, Jörn Theisel, Holger Magnork, Marcus Keim, Daniel University of Konstanz Germany TU Braunschweig Germany Telefonica o2 Business Intelligence Center Germany University of Magdeburg Germany

ISBN: (纸本)9781424452835

Visual exploration of multivariate data typically requires projection onto lower-dimensional representations. The number of possible representations grows rapidly with the number of dimensions, and manual exploration quickly becomes ineffective or even unfeasible. This paper proposes automatic analysis methods to extract potentially relevant visual structures from a set of candidate visualizations. Based on features, the visualizations are ranked in accordance with a specified user task. The user is provided with a manageable number of potentially useful candidate visualizations, which can be used as a starting point for interactive data analysis. This can effectively ease the task of finding truly useful visualizations and potentially speed up the data exploration task. In this paper, we present ranking measures for class-based as well as non class-based Scatterplots and parallel Coordinates visualizations. The proposed analysis methods are evaluated on different datasets. ©2009 ieee.

关键词： visualization

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