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ieee symposium on Biological Data visualization 2012, BioVis 2012 - Proceedings

IEEE Symposium on Biological Data Visualization 2012, BioVis...

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2nd ieee symposium on Biological Data visualization, BioVis 2012

ISBN: (纸本)9781467347303

The proceedings contain 16 papers. The topics discussed include: interactive extraction of neural structures with user-guided morphological diffusion;volume visualization in serial electron microscopy using local variance;INCIDE the brain of a bee: visualising honeybee brain activity in real time by semantic segmentation;towards real-time visualization of detailed neural tissue models: view frustum culling for parallel rendering;heterogeneity-based guidance for exploring multiscale data in systems biology;MaTSE: the microarray time-series explorer;ADVISe: visualizing the dynamics of enzyme annotations in UniProt/SwissProt;gene-RiViT: a visualization tool for comparative analysis of gene neighborhoods in prokaryote;mzRepeat: visual analysis of lipids in mass spectrometry;similarity analysis of cell movements in video microscopy;and epithelial cell reconstruction and visualization of the developing drosophila wing imaginal disc.

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Towards real-time visualization of detailed neural tissue models: View frustum culling for parallel rendering

Towards real-time visualization of detailed neural tissue mo...

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2nd ieee symposium on Biological Data visualization, BioVis 2012

作者： Hernando, Juan B. Schürmann, Felix Pastor, Luis CeSViMa Universidad Politécnica de Madrid Spain Blue Brain Project École Polytechnique Fédérale de Lausanne Switzerland GMRV Universidad Rey Juan Carlos Spain

ISBN: (纸本)9781467347303

Recent efforts to model neural tissue in great anatomical detail play an important role in the shift towards simulation-based brain research. visualization of those detailed models is an important part of the scientific workflow, allowing domain scientists to inspect and analyze the models as a virtual tissue. However, these visualizations pose several computational and interface challenges, from issues such as data size and geometrical and visual complexity. Manual or query driven selection of visual attributes such as color, transparency, transfer functions, visibility are important components for the usability of those visualizations, yet this requires the rendering to be as responsive as possible. Given the data complexity (several million triangles) - despite the power of current GPUs - parallel rendering is the only choice to visualize the full circuits at interactive levels. In particular, sort-first is an appropriate choice to deal with transparency, however it requires efficient view frustum culling. This paper presents two novel techniques for view frustum culling based on a bounding volume skeleton which is created from the geometrical skeleton of the neurons. These skeletons are combined with spatial partitions and some GPU processing to extract the portions of the neurons that need to be rendered while still facilitating interactive changes in the attributes. Experimental results show that the proposed method yields better results than classical approaches such as OBB-trees and looks promising for sort-first environments. © 2012 ieee.

关键词： visualization

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Query-driven parallel exploration of large datasets

Query-driven parallel exploration of large datasets

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2nd symposium on Large-Scale Data Analysis and visualization, LDAV 2012

作者： Atanasov, Atanas Srinivasan, Madhusudhanan Weinzierl, Tobias Technische Universität München Germany King Abdullah University of Science and Technology Germany

ISBN: (纸本)9781467347334

Recent advances in supercomputing capabilities pose a multi-faceted data retrieval challenge to the exploration and visualisation of the obtained results: the bandwidth between visualisation devices and the high-performance computing (HPC) clusters neither scales with the simulation data nor with the compute power, the total memory footprint of the data on the supercomputer often exceeds the aggregate memory on the visualisation, and the data has to be distributed among several visualisation nodes working in parallel to render a visual. In the present paper, we introduce an on-demand data exploration paradigm that leverages HPC capabilities and distributed visualisation without requiring a large memory footprint on the visualisation cluster. Regions of interest within the data are specified by the user in the form of queries. These queries, augmented by node identifiers on the visualisation cluster, are automatically distributed among multiple compute nodes of the HPC cluster. The compute nodes work in parallel to assemble and merge data in response to the user query until the data distribution matches the visualisation cluster's topology. Query results are then simultaneously streamed to the right visualisation nodes. Our approach allows for interactive exploration of data residing on HPC resources, irrespective of memory footprint. The streaming of data to the visualisation nodes scales with the bandwidth of the interconnecting network and the HPC cluster's domain decomposition, while the latter is hidden from the visualisation and can change dynamically. We demonstrate the capability of our query-driven approach with a turbulent mixing dataset, and show that it supports interactive data exploration on HPC systems. © 2012 ieee.

关键词： visualization

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Guest Editor's Introduction: Special Section on the Eurographics symposium on parallel graphics and visualization (EGPGV)

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2011年第2期17卷 130-131页

作者： Comba, Joao Weiskopf, Daniel Univ Fed Rio Grande do Sul Inst Informat Graph Grp BR-91501970 Porto Alegre RS Brazil Univ Stuttgart Visualizat Res Ctr VISUS D-70569 Stuttgart Germany

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ConnectedCharts: Explicit visualization of relationships between data graphics

ConnectedCharts: Explicit visualization of relationships bet...

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14th Eurographics Conference on visualization 2012, EuroVis 2012

作者： Viau, C. McGuffin, M.J. École de Technologie Supérieure Canada

Multidimensional multivariate data can be visualized using many different well-known charts, such as bar charts, stacked bar charts, grouped bar charts, scatterplots, or pivot tables, or also using more advanced highdimensional techniques such as scatterplot matrices (SPLOMs) or parallel coordinate plots (PCPs). These many techniques have different advantages, and users may wish to use several charts or data graphics to understand a dataset from different perspectives. We present ConnectedCharts, a technique for displaying relationships between multiple charts. ConnectedCharts allow for hybrid combinations of bar charts, scatterplots, and parallel coordinates, with curves drawn to show the conceptual links between charts. The charts can be thought of as coordinated views, where linking is achieved not only through interactive brushing, but also with explicitly drawn curves that connect corresponding data tuples or axes. We present a formal description of a design space of many simple charts, and also identify different kinds of connections that can be displayed between related charts. Our prototype implementation demonstrates how the connections between multiple charts can make relationships clearer and can serve to document the history of a user's analytical process, leading to potential applications in visual analytics and dashboard design. © 2012 The Author(s).

关键词： visualization

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Porosity maps - Interactive exploration and visual analysis of porosity in carbon fiber reinforced polymers

Porosity maps - Interactive exploration and visual analysis ...

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14th Eurographics Conference on visualization 2012, EuroVis 2012

作者： Reh, A. Plank, B. Kastner, J. Gröller, E. Heinzl, C. University of Applied Sciences Upper Austria Campus Wels Austria Vienna University of Technology Institute of Computer Graphics and Algorithms Vienna Austria

In this work a novel method for the characterization of porosity in carbon fiber reinforced polymers (CFRP) is presented. A visualization pipeline for the interactive exploration and visual analysis of CFRP specimens is developed to enhance the evaluation workflow for non-destructive testing (NDT) practitioners based on specified tasks. Besides quantitative porosity determination and the calculation of local pore properties, i.e., volume, surface, dimensions and shape factors, we employ a drill-down approach to explore pores in a CFRP specimen. We introduce Porosity Maps (PM), to allow for a fast porosity evaluation of the specimen. Pores are filtered in two stages. First a region of interest is selected in the porosity maps. Second, pores are filtered with parallel coordinates according to their local properties. Furthermore a histogram-based best-viewpoint widget was implemented to visualize the quality of viewpoints on a sphere. The advantages of our approach are demonstrated using real world CFRP specimens. We are able to show that our visualization-driven approach leads to a better evaluation of CFRP components than existing reference methods. © 2012 The Author(s).

关键词： Porosity

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A flexible Java GPU-enhanced visualization framework and its applications

A flexible Java GPU-enhanced visualization framework and its...

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Annual ieee symposium on Computer-Based Medical Systems

作者： Ruida Cheng Justin Senseney Nishith Pandya Evan McCreedy Matthew J. McAuliffe Alexandra Bokinsky Imaging Sciences Laboratory Center for Information Technology National Institutes of Health DHHS USA Geometric Tools Inc. Chapel Hill NC USA

A flexible biomedical visualization framework implemented with Java, OpenGL, and OpenCL performs efficient volume rendering with large, multi-modal datasets. The framework takes advantage of the parallel processing power on modern graphics hardware with novel OpenCL and GLSL shading language implementations. The Java and GPU environment provide portable advanced biomedical image visualization applications. Several applications built on top of the GPU framework are also presented to show the extensibility of the application. These include multi-surface rendering, stereoscopic rendering, image fusion, and diffusion tensor visualization.

关键词： Rendering (computer graphics) graphics processing unit Surface treatment Image color analysis Java visualization Pipelines

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Progressive parallel coordinates

Progressive parallel coordinates

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Pacific (formerly Asia-Pacific APVIS) visualization symposium

作者： René Rosenbaum Jian Zhi Bernd Hamann Visual Computing and Computer Graphics group (VCG) Institute for Computer Science University of Rostock Rostock Germany Institute for Data Analysis and Visualization (IDAV) Department of Computer Science University of California Davis CA USA Department of Industrial Engineering and Operations Research Columbia University NY USA

Progressive refinement is a methodology that makes it possible to elegantly integrate scalable data compression, access, and presentation into one approach. Specifically, this paper concerns the effective use of progressive parallel coordinates (PPCs), utilized routinely for high-dimensional data visualization. It discusses how the power of the typical stages of progressive data visualization can also be utilized fully for PPCs. Further, different implementations of the underlying methods and potential application domains are described. The paper also presents empirical results concerning the benefits of PPC with regard to efficient data management and improved presentation, indicating that the proposed approach is able to close the gap between data handling and visualization.

关键词： Lead visualization Logic gates

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Towards real-time visualization of detailed neural tissue models: View frustum culling for parallel rendering

Towards real-time visualization of detailed neural tissue mo...

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ieee symposium on Biological Data visualization (BioVis)

作者： Juan B. Hernando Felix Schürmann Luis Pastor CeSViMa Universidad Politécnica de Madrid Spain Blue Brain Project École Polytechnique Fédérale de Lausanne Switzerland GMRV Universidad Rey Juan Carlos de Madrid Spain

关键词： Skeleton Neurons Rendering (computer graphics) Computational modeling Octrees Arrays graphics processing units

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GPGPU implementation of visual tracking by particle filter with pixel ratio likelihood

GPGPU implementation of visual tracking by particle filter w...

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ieee/SICE International symposium on System Integration

作者： Norikazu Ikoma Takashi Ito Faculty of Engineering Kyushu Institute of Technology Fukuoka Japan

Visual tracking by particle filter with pixel ratio in a region of interest for likelihood computation has wide range of applications despite of its simple algorithm. A GPGPU (General Purpose computation on graphics Processing Unit) implementation of the visual tracking in parallel computation has been proposed in this paper. Algorithm of the tracker has almost fully been implemented in CUDA framework. Difference of the proposed algorithm from the full algorithm is a reduction of image size from the original image in order to deal with multiple images for likelihood computation in limited size of constant memory of the GPU hardware. Performance of the proposed method achieves 30 fps (frame per second) for specific colored object tracing task and more than ten frame per second for a task of hands tracking of a car driver operating a steering.

关键词： graphics processing units visualization Object tracking Image color analysis Vehicles Computational modeling Mathematical model

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