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multivariate visualization for atmospheric pollution

JOURNAL OF visualization 2019年第6期22卷 1093-1105页

作者： Lu, Daying Ge, Yao Wang, Laihua Zhu, Dengming Wang, Zhaoqi Yuan, Xiaoru Qufu Normal Univ Coll Software Qufu Shandong Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Peking Univ Key Lab Machine Percept Beijing Peoples R China

multivariate visualization for atmospheric pollution is a challenging research topic. Appropriate algorithms and data structures based on modern graphics hardware are used to obtain high performance. 3D visualization of the atmospheric wind field and pollutant concentrations can easily result in visual perception problems such as occlusion and cluttering even artifacts. To solve the above issues, a K-means clustering technique is used in combination with a similarity metric between streamlines based on an iterative closest point method to cluster the initial streamlines. A small set of streamlines is then selected to represent the prominent structure of the wind field. The proper illumination model and the depth sorting method reduce the inter-occlusion between streamlines and isosurfaces to show much clearer wind field pattern and important features effectively. The atmospheric pollution data set is employed to evaluate the proposed algorithm framework.

关键词： multivariate visualization Atmospheric pollution Occlusion Streamline Isosurface

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Surveying design spaces with performance maps: A multivariate visualization method for parametric design and architectural design optimization

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INTERNATIONAL JOURNAL OF ARCHITECTURAL COMPUTING 2017年第1期15卷 38-53页

作者： Wortmann, Thomas Singapore Univ Technol & Design 8 Somapah Rd Singapore 487372 Singapore

This article presents a method to visualize high-dimensional parametric design spaces with applications in computational design processes and interactive optimization. The method extends Star Coordinates using a triangulation-based interpolation with Barycentric Coordinates. It supports the understanding of design problems in architectural design optimization by allowing designers to move between a high-dimensional design space and a low-dimensional Performance Map. This Performance Map displays the characteristics of the fitness landscape, develops designers' intuitions about the relationships between design parameters and performance, allows designers to examine promising design variants, and delineates promising areas for further design exploration.

关键词： Fitness landscape design space exploration multivariate visualization optimization Star Coordinates

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Bimodal visualization of Industrial X-Ray and Neutron Computed Tomography Data

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2025年第4期31卷 2196-2210页

作者： Huang, Xuan Miao, Haichao Kim, Hyojin Townsend, Andrew Champley, Kyle Tringe, Joseph Pascucci, Valerio Bremer, Peer-Timo Univ Utah SCI Inst Salt Lake City UT 84112 USA Lawrence Livermore Natl Lab Ctr Appl Sci Comp Livermore CA 94550 USA Lawrence Livermore Natl Lab Nondestruct Characterizat Inst Livermore CA 94550 USA

Advanced manufacturing creates increasingly complex objects with material compositions that are often difficult to characterize by a single modality. Our collaborating domain scientists are going beyond traditional methods by employing both X-ray and neutron computed tomography to obtain complementary representations expected to better resolve material boundaries. However, the use of two modalities creates its own challenges for visualization, requiring either complex adjustments of bimodal transfer functions or the need for multiple views. Together with experts in nondestructive evaluation, we designed a novel interactive bimodal visualization approach to create a combined view of the co-registered X-ray and neutron acquisitions of industrial objects. Using an automatic topological segmentation of the bivariate histogram of X-ray and neutron values as a starting point, the system provides a simple yet effective interface to easily create, explore, and adjust a bimodal visualization. We propose a widget with simple brushing interactions that enables the user to quickly correct the segmented histogram results. Our semiautomated system enables domain experts to intuitively explore large bimodal datasets without the need for either advanced segmentation algorithms or knowledge of visualization techniques. We demonstrate our approach using synthetic examples, industrial phantom objects created to stress bimodal scanning techniques, and real-world objects, and we discuss expert feedback.

关键词： Neutrons Histograms visualization Transfer functions Computed tomography Rendering (computer graphics) Image segmentation multivariate visualization visualization application image segmentation volume visualization

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Immersive representation for visualizing surface temperature and integrative lighting in architecture

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BUILDING AND ENVIRONMENT 2024年 262卷

作者： Tabatabaeifard, Seyed Amin Lalonde, Jean-Francois Hebert, Marc Potvin, Andre Demers, Claude M. H. Laval Univ Sch Architecture GRAP Grp Rech Ambiances Phys Quebec City PQ Canada Univ Laval Dept Elect & Comp Engn Comp Vis & Syst Lab Quebec City PQ Canada Univ Laval Fac Med CERVO Brain Res Ctr Quebec City PQ Canada

This paper illustrates the potential of representing and reading environmental data captured for immersive visualization of indoor built environments. This study introduces methods for qualitative representation of light and heat in aligned viewing directions in immersive scenes. It employs a novel technique for capturing High Dynamic Range (HDR) and thermal images in 360-degree directions. This technique allows visualization of radiant temperature and integrative lighting variations associated with the viewing direction and time. The highlight of these visualizations is the identical viewing points in studying the indoor ambiances. The paper provides visualizations derived from hourly data captures in architectural studios through a 360-degree thermalvisual capturing device. The paper aims to present these results through various visualization formats, including architectural planar presentations, diagrams, and colour maps, showing surface temperature and Photopic and Melanopic illuminance intensities. Architectural insights gained from each of these visualizations are highlighted and discussed. Specifically, the results of this research illustrate the potential of the immersive image-based environmental assessment and visualization method for representing indoor ambiances regarding their nonvisible thermal and lighting conditions through time and across all viewing directions within the space.

关键词： multivariate visualization 360-Degree imaging Integrative lighting Immersive representation Spherical thermal imaging

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Terrain trees: a framework for representing, analyzing and visualizing triangulated terrains

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GEOINFORMATICA 2023年第3期27卷 525-564页

作者： Fellegara, Riccardo Iuricich, Federico Song, Yunting De Floriani, Leila German Aerosp Ctr DLR Inst Software Technol Dept Software Space Syst & Interact Visualizat Braunschweig Germany Clemson Univ Sch Comp Clemson SC USA Univ Maryland Dept Geog Sci College Pk MD 20742 USA Univ Maryland College Pk MD 20742 USA

We propose a family of spatial data structures for the representation and processing of Triangulated Irregular Networks (TINs). We call such data structures Terrain trees. A Terrain tree combines a minimal encoding of the connectivity of the TIN with a hierarchical spatial index. Connectivity relations are extracted locally at run-time, within each leaf block of the hierarchy, based on specific application needs. Spatial queries are performed by exploring the hierarchical data structure. We present a new framework for terrain analysis based on Terrain trees. The framework, implemented in the Terrain trees library (TTL), contains algorithms for morphological features extraction, such as roughness and curvature, and for topology-based analysis of terrains. Moreover, it includes a technique for multivariate visualization, which enables the analysis of multiple scalar fields defined on the same terrain. To prove the effectiveness and scalability of such framework, we have compared the different Terrain trees against each other and also against the most compact state-of-the-art data structure for TINs. Comparisons are performed on storage and generation costs and on the efficiency in performing terrain analysis operations.

关键词： Terrain modeling Triangulated irregular networks (TINs) Spatial indexes Terrain analysis multivariate visualization

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2.5D Dust & Magnet visualization for Large multivariate Data 20

2.5D Dust & Magnet Visualization for Large Multivariate Data

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13th International Symposium on Visual Information Communication and Interaction

作者： Vollmer, Jan Ole Doellner, Juergen Univ Potsdam Hasso Plattner Inst Fac Digital Engn Potsdam Germany

ISBN: (纸本)9781450387507

In this paper, we present a 2.5D visualization technique based on the dust & magnet metaphor, which generally allows for interactively exploring and analyzing large multivariate data sets. In addition to position and color, we introduce height as additional visual variable for particles to encode extra data attributes in the 2.5D visualization, thus increasing the potential for identifying correlations between attributes. Further, we have developed a real-time collision detection algorithm as part of the particle simulation that ensures overlap-free particle positioning, thereby enabling the continuous perception of patterns, clusters, and outliers. These extensions facilitate on-the-fly validation of hypotheses through the highly dynamic configuration of magnets and visual attribute encoding, which also allows for a better integration of the user's domain knowledge. We demonstrate the application of our visualization technique using various real-world data sets from different domains, e.g., finance and software analytics.

关键词： multivariate visualization 2.5D dimensionality reduction interactive

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Guided Decision Tree: A Tool to Interactively Create Decision Trees Through visualization of Subsequent LDA Diagrams

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APPLIED SCIENCES-BASEL 2024年第22期14卷 10497页

作者： Mohedano-Munoz, Miguel A. Raya, Laura Sanchez, Alberto Estn Biol Donana CSIC Seville 41092 Spain U tad Fac Engn Madrid 28290 Spain Univ Rey Juan Carlos Dept Comp Sci & Stat Madrid 28933 Spain

Featured Application The developed tool can be applied to motion recognition in individuals to accurately identify the exercises they are performing. This application is particularly useful in fields such as sports science, physical therapy, fitness tracking, and Virtual Reality, where understanding and monitoring exercise routines and movement are *** Decision trees are a widely used machine learning technique due to their ease of interpretation and construction. This method allows domain experts to learn from raw data, but they cannot include their prior knowledge in the analysis due to its automatic nature, which implies minimal human intervention in its computation. Conversely, interactive visualization methods have proven to be effective in gaining insights from data, as they incorporate the researcher's criteria into the analysis process. In an effort to combine both methodologies, we have developed a tool to manually build decision trees according to subsequent visualizations of data mapping after applying linear discriminant analysis in combination with Star Coordinates in order to analyze the importance of each feature in the separation. The nodes' information contains data about the features that can be used to split and their cut-off values, in order to select them in a guided manner. In this way, it is possible to produce simpler and more expertly driven decision trees than those obtained by automatic methods. The resulting decision trees reduces the tree size compared to those generated by automatic machine learning algorithms, obtaining a similar accuracy and therefore improving their understanding. The tool developed and presented here to manually create decision trees in a guided manner based on the subsequent visualizations of the data mapping facilitates the use of this method in real-world applications. The usefulness of this tool is demonstrated through a case study with a complex dataset used for motion recognition, where domain exp

关键词： multivariate visualization decision trees visual data mining linear discriminant analysis motion recognition

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AgentVis: Visual Analysis of Agent Behavior With Hierarchical Glyphs

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2021年第9期27卷 3626-3643页

作者： Rees, Dylan Laramee, Robert S. Brookes, Paul D'Cruze, Tony Smith, Gary A. Miah, Aslam Swansea Univ Swansea SA2 8PP W Glam Wales Univ Nottingham Nottingham NG7 2RD England QPC Ltd Mold CH7 1YA England Aria Solut Calgary AB T2R 0G7 Canada Admiral Grp Plc Llansamlet Swansea SA1 8AG W Glam Wales

Glyphs representing complex behavior provide a useful and common means of visualizing multivariate data. However, due to their complex shape, overlapping, and occlusion of glyphs is a common and prominent limitation. This limits the number of discreet data tuples that can be displayed in a given image. Using a real-world application, glyphs are used to depict agent behavior in a call center. However, many call centers feature thousands of agents. A standard approach representing thousands of agents with glyphs does not scale. To accommodate the visualization incorporating thousands of glyphs we develop clustering of overlapping glyphs into a single parent glyph. This hierarchical glyph represents the mean value of all child agent glyphs, removing overlap and reduTcing visual clutter. Multi-variate clustering techniques are explored and developed in collaboration with domain experts in the call center industry. We implement dynamic control of glyph clusters according to zoom level and customized distance metrics, to utilize image space with reduced overplotting and cluttering. We demonstrate our technique with examples and a usage scenario using real-world call-center data to visualize thousands of call center agents, revealing insight into their behavior and reporting feedback from expert call-center analysts.

关键词： Data visualization Industries visualization Clutter Collaboration Measurement Shape Glyph clustering multivariate visualization

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Data-Driven Space-Filling Curves

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2021年第2期27卷 1591-1600页

作者： Zhou, Liang Johnson, Chris R. Weiskopf, Daniel Peking Univ Natl Inst Hlth Data Sci Beijing Peoples R China Univ Utah SO Inst Salt Lake City UT 84112 USA Univ Stuttgart Visualizat Res Ctr VLSUS Stuttgart Germany

-We propose a data-driven space-filling curve method for 2D and 3D visualization. Our flexible curve traverses the data elements in the spatial domain in a way that the resulting linearization better preserves features in space compared to existing methods. We achieve such data coherency by calculating a Hamiltonian path that approximately minimizes an objective function that describes the similarity of data values and location coherency in a neighborhood. Our extended variant even supports multiscale data via quadtrees and octrees. Our method is useful in many areas of visualization including multivariate or comparative visualization ensemble visualization of 2D and 3D data on regular grids or multiscale visual analysis of particle simulations. The effectiveness of our method is evaluated with numerical comparisons to existing techniques and through examples of ensemble and multivariate datasets.

关键词： Three-dimensional displays Two dimensional displays Data visualization Brushes Linear programming Rendering (computer graphics) Faces Space-filling curves comparative visualization ensemble visualization multivariate visualization

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Feature Level-Sets: Generalizing Iso-Surfaces to Multi-Variate Data

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2020年第2期26卷 1308-1319页

作者： Jankowai, Jochen Hotz, Ingrid Linkoping Inst Technol Dept Sci & Technol S-60233 Norrkoping Sweden

Iso-surfaces or level-sets provide an effective and frequently used means for feature visualization. However, they are restricted to simple features for uni-variate data. The approach does not scale when moving to multi-variate data or when considering more complex feature definitions. In this paper, we introduce the concept of traits and feature level-sets, which can be understood as a generalization of level-sets as it includes iso-surfaces, and fiber surfaces as special cases. The concept is applicable to a large class of traits defined as subsets in attribute space, which can be arbitrary combinations of points, lines, surfaces and volumes. It is implemented into a system that provides an interface to define traits in an interactive way and multiple rendering options. We demonstrate the effectiveness of the approach using multi-variate data sets of different nature, including vector and tensor data, from different application domains.

关键词： Tensile stress Data visualization Rendering (computer graphics) Transfer functions Geometry Feature extraction multivariate visualization visualization techniques and methodologies approximation of surfaces and contours

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