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Spatio-Temporal Feature Exploration in Combined Particle/volume Reference Frames

ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2017年第6期23卷 1624-1635页

作者： Sauer, Franz Ma, Kwan-Liu Univ Calif Davis Dept Comp Sci Davis CA 95616 USA

The use of large-scale scientific simulations that can represent physical systems using both particle and volume data simultaneously is gaining popularity as each of these reference frames has an inherent set of advantages when studying different phenomena. Furthermore, being able to study the dynamic evolution of these time varying data types is an integral part of nearly all scientific endeavors. However, the techniques available to scientists generally limit them to studying each reference frame separately making it difficult to draw connections between the two. In this work we present a novel method of feature exploration that can be used to investigate spatio-temporal patterns in both data types simultaneously. More specifically, we focus on how spatio-temporal subsets can be identified from both reference frames, and develop new ways of visually presenting the embedded information to a user in an intuitive manner. We demonstrate the effectiveness of our method using case studies of real world scientific datasets and illustrate the new types of exploration and analyses that can be achieved through this technique.

关键词： Particle data volume data feature exploration spatio-temporal analysis

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Smart Surrogate Widgets for Direct volume Manipulation

Smart Surrogate Widgets for Direct Volume Manipulation

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Pacific (formerly Asia-Pacific APVIS) visualization symposium

作者： Sergej Stoppel Stefan Bruckner University of Bergen

Interaction is an essential aspect in volume visualization, yet common manipulation tools such as bounding boxes or clipping plane widgets provide rather crude tools as they neglect the complex structure of the underlying data. In this paper, we introduce a novel volume interaction approach based on smart widgets that are automatically placed directly into the data in a visibility-driven manner. By adapting to what the user actually sees, they act as proxies that allow for goal-oriented modifications while still providing an intuitive set of simple operations that is easy to control. In particular, our method is well-suited for direct manipulation scenarios such as touch screens, where traditional user interface elements commonly exhibit limited utility. To evaluate out approach we conducted a qualitative user study with nine participants with various backgrounds.

关键词： Data visualization Three-dimensional displays Shape Tools Transfer functions Rendering (computer graphics) Lenses

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Transfer Function Design Toolbox for Full-Color volume Datasets 10

Transfer Function Design Toolbox for Full-Color Volume Datas...

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ieee Pacific visualization symposium (ieee PacificVis)

作者： Falk, Martin Hotz, Ingrid Ljung, Patric Treanor, Darren Ynnerman, Anders Lundstrom, Claes Linkoping Univ Dept Sci & Technol Linkoping Sweden Linkoping Univ Ctr Med Image Sci & Visualizat CMIV Linkoping Sweden Leeds Teaching Hosp NHS Trust Leeds W Yorkshire England Sectra AB Linkoping Sweden

ISBN: (纸本)9781509057382

In this paper, we tackle the challenge of effective Transfer Function (TF) design for Direct volume Rendering (DVR) of full-color datasets. We propose a novel TF design toolbox based on color similarity which is used to adjust opacity as well as replacing colors. We show that both CIE L*u*v* chromaticity and the chroma component of YCBCR are equally suited as underlying color space for the TF widgets. In order to maximize the area utilized in the TF editor, we renormalize the color space based on the histogram of the dataset. Thereby, colors representing a high er share of the dataset are depicted more prominently, thus providing a higher sensitivity for fine-tuning TF widgets. The applicability of our TF design toolbox is demonstrated by volume ray casting challenging full-color volume data including the visible male cryosection dataset and examples from 3D histology.

关键词： Computer graphics [I.3.3]: Picture/Image Generation-Display algorithms Computer graphics [I.3.6]: Methodology and Techniques Computer graphics [I. 3.7] : ThreeDimensional graphics and Realism Computer graphics [I.3.8]: Applications

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Efficient GPU-Accelerated Computation of Isosurface Similarity Maps 10

Efficient GPU-Accelerated Computation of Isosurface Similari...

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ieee Pacific visualization symposium (ieee PacificVis)

作者： Imre, Martin Tao, Jun Wang, Chaoli Univ Notre Dame Notre Dame IN 46556 USA

ISBN: (纸本)9781509057382

We present an efficient GPU-based solution to compute isosurface similarity maps for scientific volume data sets. Our approach first replaces exact isosurface extraction with a binary volume indicating whether each voxel intersects the surface or not. We then employ bounding volume hierarchy (BVH)-trees to speed up the distance field computation. Finally, a self-similarity map is generated from which we identify representative isosurfaces. We apply our approach to compute isosurface similarity maps from different volume data sets of varying sizes and characteristics. The results demonstrate significant speed gain with acceptable loss of accuracy, showing the potential of our solution for handling large-scale time-varying multivariate data sets.

关键词： Isosurfaces graphics processing units Mutual information Histograms Combustion Upper bound Rendering (computer graphics)

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Parallel Partial Reduction for Large-Scale Data Analysis and visualization

Parallel Partial Reduction for Large-Scale Data Analysis and...

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ieee symposium on Large Data Analysis and visualization (LDAV)

作者： Wenbin He Hanqi Guo Tom Peterka Sheng Di Franck Cappello Han-Wei Shen Department of Computer Science and Engineering The Ohio State University Columbus OH USA Mathematics and Computer Science Division Argonne National Laboratory Lemont IL USA

ISBN: (纸本)9781538668740

We present a novel partial reduction algorithm to aggregate sparsely distributed intermediate results that are generated by data-parallel analysis and visualization algorithms. Applications of partial reduction include flow trajectory analysis, big data online analytical processing, and volume rendering. Unlike traditional full parallel reduction that exchanges dense data across all processes, the purpose of partial reduction is to exchange only intermediate results that correspond to the same query, such as line segments of the same flow trajectory. To this end, we design a three-stage algorithm that minimizes the communication cost: (1) partitioning the result space into groups; (2) constructing and optimizing the reduction partners for each group; and (3) initiating collective reduction operations for all groups concurrently. Both theoretical and empirical analyses show that our algorithm outperforms the traditional methods when the intermediate results are sparsely distributed. We also demonstrate the effectiveness of our algorithm for flow visualization, big log data analysis, and volume rendering.

关键词： Data visualization Distributed databases Rendering (computer graphics) Trajectory Data analysis Histograms Parallel processing

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Multivariate volumetric Data Analysis and visualization through Bottom-Up Subspace Exploration 10

Multivariate Volumetric Data Analysis and Visualization thro...

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ieee Pacific visualization symposium (ieee PacificVis)

作者： Lu, Kewei Shen, Han-Wei Ohio State Univ Columbus OH 43210 USA

ISBN: (纸本)9781509057382

Multivariate volumetric datasets are often encountered in results generated by scientific simulations. Compared to univariate datasets, analysis and visualization of multivariate datasets are much more challenging due to the complex relationships among the variables. As an effective way to visualize and analyze multivariate datasets, volume rendering has been frequently used, although designing good multivariate transfer functions is still non-trivial. In this paper, we present an interactive workflow to allow users to design multivariate transfer functions. To handle large scale datasets, in the preprocessing stage we reduce the number of data points through data binning and aggregation, and then a new set of data points with a much smaller size are generated. The relationship between all pairs of variables is presented in a matrix juxtaposition view, where users can navigate through the different subspaces. An entropy based method is used to help users to choose which subspace to explore. We proposed two weights: scatter weight and size weight that are associated with each projected point in those different subspaces. Based on those two weights, data point filter and kernel density estimation operations are employed to assist users to discover interesting features. For each user-selected feature, a Gaussian function is constructed and updated incrementally. Finally, all those selected features are visualized through multivariate volume rendering to reveal the structure of data. With our system, users can interactively explore different subspaces and specify multivariate transfer functions in an effective way. We demonstrate the effectiveness of our system with several multivariate volumetric datasets.

关键词： Transfer functions Data visualization Rendering (computer graphics) Image color analysis Estimation Entropy Kernel

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Functional Thin Films on Surfaces

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2017年第3期23卷 1179-1192页

作者： Vantzos, Orestis Azencot, Omri Wardeztky, Max Rumpf, Martin Ben-Chen, Mirela Technion Israel Inst Technol Dept Comp Sci IL-3200003 Haifa Israel Univ Gottingen Inst Numer & Appl Math D-37073 Gottingen Germany Univ Bonn Inst Numer Simulat D-53113 Bonn Germany

The motion of a thin viscous film of fluid on a curved surface exhibits many intricate visual phenomena, which are challenging to simulate using existing techniques. A possible alternative is to use a reduced model, involving only the temporal evolution of the mass density of the film on the surface. However, in this model, the motion is governed by a fourth-order nonlinear PDE, which involves geometric quantities such as the curvature of the underlying surface, and is therefore difficult to discretize. Inspired by a recent variational formulation for this problem on smooth surfaces, we present a corresponding model for triangle meshes. We provide a discretization for the curvature and advection operators which leads to an efficient and stable numerical scheme, requires a single sparse linear solve per time step, and exactly preserves the total volume of the fluid. We validate our method by qualitatively comparing to known results from the literature, and demonstrate various intricate effects achievable by our method, such as droplet formation, evaporation, droplets interaction and viscous fingering. Finally, we extend our method to incorporate non-linear van der Waals forcing terms which stabilize the motion of the film and allow additional effects such as pearling.

关键词： Computer graphics three-dimensional graphics and realism animation

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A Visual Analytics System for Brain Functional Connectivity Comparison across Individuals, Groups, and Time Points 10

A Visual Analytics System for Brain Functional Connectivity ...

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ieee Pacific visualization symposium (ieee PacificVis)

作者： Fujiwara, Takanori Chou, Jia-Kai McCullough, Andrew M. Ranganath, Charan Ma, Kwan-Liu Univ Calif Davis Davis CA 95616 USA

ISBN: (纸本)9781509057382

Neuroscientists study brain functional connectivity in order to obtain a deeper understanding of how the brain functions. Current studies are mainly based on analyzing the averaged brain connectivity of a group (or groups) due to the high complexity of the collected data in terms of dimensionality, variability, and volume. While it is more desirable for the researchers to explore the potential variability between individual subjects or groups, a data analysis solution meeting this need is absent. In this paper, we present the design and capabilities of such a visual analytics system, which enables neuroscientists to visually compare the differences of brain networks between individual subjects as well as group averages, to explore a large dataset and examine sub-groups of participants that may not have been expected a priori to be of interest, to review detailed information as needed, and to manipulate the data and views to fit their analytical needs with easy interactions. We demonstrate the utility and strengths of this system with case studies using a representative functional connectivity dataset.

关键词： I.3.8 [Computer graphics]: Applications

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Image and Distribution Based volume Rendering for Large Data Sets

Image and Distribution Based Volume Rendering for Large Data...

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Pacific (formerly Asia-Pacific APVIS) visualization symposium

作者： Ko-Chih Wang Naeem Shareef Han-Wei Shen The Ohio State University

Analyzing scientific datasets created from simulations on modern supercomputers is a daunting challenge due to the fast pace at which these datasets continue to grow. Low cost post analysis machines used by scientists to view and analyze these massive datasets are severely limited by their deficiencies in storage bandwidth, capacity, and computational power. Trying to simply move these datasets to these platforms is infeasible. Any approach to view and analyze these datasets on post analysis machines will have to effectively address the inevitable problem of data loss. Image based approaches are well suited for handling very large datasets on low cost platforms. Three challenges with these approaches are how to effectively represent the original data with minimal data loss, analyze the data in regards to transfer function exploration, which is a key analysis tool, and quantify the error from data loss during analysis. We present a novel image based approach using distributions to preserve data integrity. At each view sample, view dependent data is summarized at each pixel with distributions to define a compact proxy for the original dataset. We present this representation along with how to manipulate and render large scale datasets on post analysis machines. We show that our approach is a good trade off between rendering quality and interactive speed and provides uncertainty quantification for the information that is lost.

关键词： Data visualization Transfer functions Histograms Uncertainty Rendering (computer graphics) Data analysis Entropy

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Towards an Adaptive Framework for Real-Time visualization of Streaming Big Data

Towards an Adaptive Framework for Real-Time Visualization of...

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19th Eurographics / ieee VGTC Conference on visualization, EuroVis 2017

作者： Khan, Amin M. Gonçalves, Daniel Leão, Duarte C. Pentaho Corporation Lisbon Portugal INESC-ID Lisboa Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

ISBN: (纸本)9783038680444

Big data poses new challenges and the need for flexible, interactive, and dynamic visualization techniques. Existing approaches, especially in enterprise data visualization with static graphics or interactive dashboards, are limited at the scale of big data, given the volume and diversity of data to consider. Streaming data further compounds on the problem with the need for real-time analytics and visualizations. On the data acquisition and collection side of things, traditional business analytics platforms are being extended with support for technologies such as Apache Spark for improvement in performance. However, for real-time data visualization for streaming data, it is necessary to go beyond Apache Spark with in-memory processing and new data visualization idioms. We propose a framework for the dynamic visualization of real-time streaming big data, resilient to both its volume and rate of change. Some of the different directions we explore include: (a) the efficient processing and consumption of streaming data;(b) the automated detection of relevant changes in the data stream, highlighting entities that merit a detailed analysis;(c) the choice of the best idioms to visualize big data, possibly leading to the development of new visualization idioms;(d) real-time visualization changes. © 2017 The Author(s) Eurographics Proceedings © 2017 The Eurographics Association.

关键词： Big data

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