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检索条件"任意字段=IEEE Symposium on Large Data Analysis and Visualization"

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Parallel Processing and Immersive visualization of Sonar Point Clouds 4

Parallel Processing and Immersive Visualization of Sonar Poi...

引用

ieee symposium on large data analysis and visualization

作者： Febretti, Alessandro Richmond, Kristof Doran, Peter Johnson, Andrew Univ Illinois Elect Visualizat Lab Chicago IL 60607 USA Frontier Astronaut LLC Chugwater WY USA Univ Illinois Dept Environm Sci Chicago IL USA

ISBN: (纸本)9781479952151

The investigation of underwater structures and natural features through Autonomous Underwater Vehicles (AUVs) is an expanding field with applications in archaeology, engineering, environmental sciences and astrobiology. Processing and analyzing the raw sonar data generated by automated surveys is challenging due to the presence of complex error sources like water chemistry, zero-depth variations, inertial navigation errors and multipath reflections. Furthermore, the complexity of the collected data makes it difficult to perform effective analysis on a standard display. Point clouds made up of hundreds of millions to billions of points are not uncommon. Highly interactive, immersive visualization is a desirable tool that researchers can use to improve the quality of a final sonar-based data product. In this paper we present a scalable toolkit for the processing and visualization of sonar point clouds on a cluster-based, large scale immersive visualization environment. The cluster is used simultaneously as a parallel processing platform that performs sonar beam-tracing of the source raw data, and as the rendering driver of the immersive display.

关键词： data visualisation geophysics computing hydrological techniques lakes parallel processing rendering (computer graphics) sonar signal processing automated surveys cluster-based immersive visualization environment immersive display rendering driver sonar beam-tracing sonar point clouds Acoustic beams Antarctica data visualization Lakes Sonar Sonar navigation Three-dimensional displays PARALLEL PROCESSING (COMPUTERS) data visualisation sonar three-dimensional displays Acoustic beams lakes sonar signal processing geophysics computing hydrological techniques Antarctica Rendering (computer graphics) visualization

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An Entropy-Based Approach for Identifying User-Preferred Camera Positions 11

An Entropy-Based Approach for Identifying User-Preferred Cam...

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ieee 11th symposium on large data analysis and visualization (LDAV)

作者： Marsaglia, Nicole Kawakami, Yuya Schwartz, Samuel D. Fields, Stefan Childs, Hank Univ Oregon Eugene OR 97403 USA

ISBN: (纸本)9781665432832

Viewpoint Quality (VQ) metrics have the potential to predict human preferences for camera placement. With this study, we introduce new VQ metrics that incorporate entropy, and explore how they can be used in combination. Our evaluation involves three phases: (1) creating a database of isosurface imagery from ten large, scientific data sets, (2) conducting a user study with approximately 30 large data visualization experts who provided over 1000 responses, and (3) analyzing how our entropy-based VQ metrics compared with existing VQ metrics in predicting expert preference. In terms of findings, we find that our entropy-based metrics are able to predict expert preferences 68% of the time, while existing VQ metrics perform much worse (52%). This finding, while valuable on its own, also opens the door for future work on in situ camera placement. Finally, as another important contribution, this work has the most extensive evaluation to date of existing VQ metrics to predict expert preference for visualizations of large, scientific data sets.

关键词： Viewpoint Quality Metrics View-Dependent visualization Automating visualization

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Galaxy: Asynchronous Ray Tracing for large High-Fidelity visualization 8

Galaxy: Asynchronous Ray Tracing for Large High-Fidelity Vis...

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8th ieee symposium on large-Scale data analysis and visualization (LDAV)

作者： Abram, Greg Navratil, Paul Grossett, Pascal Rogers, David Ahrens, James Texas Adv Comp Ctr Austin TX 78758 USA Los Alamos Natl Lab Los Alamos NM USA

ISBN: (纸本)9781538668733

We present Galaxy, a fully asynchronous distributed parallel rendering engine geared towards using full global illumination for large-scale visualization. Galaxy provides performant distributed rendering of complex lighting and material models, particularly those that require ray traversal across nodes. Our design is favorable for tightly-coupled in situ scenarios, where data remains on simulation nodes. By employing asynchronous framebuffer updates and a novel subtractive lighting model, we achieve acceptable image quality from the first ray generation, and improve quality throughout the render epoch. On simulated in situ rendering tasks, Galaxy outperforms the current best-of-breed scientific ray tracer by over 3x for distributed geometric and particle data, while providing expanded rendering capability for global illumination and complex materials.

关键词： Human-Centered Computing visualization Computer Graphics Rendering Ray Tracing

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Multivariate Volume visualization through Dynamic Projections 4

Multivariate Volume Visualization through Dynamic Projection...

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ieee symposium on large data analysis and visualization

作者： Liu, Shusen Wang, Bei Thiagarajan, Jayaraman J. Bremer, Peer-Timo Pascucci, Valerio Univ Utah SCI Inst Salt Lake City UT 84112 USA Lawrence Livermore Natl Lab Livermore CA USA

ISBN: (纸本)9781479952151

We propose a multivariate volume visualization framework that tightly couples dynamic projections with a high-dimensional transfer function design for interactive volume visualization. We assume that the complex, high- dimensional data in the attribute space can be well-represented through a collection of low-dimensional linear subspaces, and embed the data points in a variety of 2D views created as projections onto these subspaces. Through dynamic projections, we present animated transitions between different views to help the user navigate and explore the attribute space for effective transfer function design. Our framework not only provides a more intuitive understanding of the attribute space but also allows the design of the transfer function under multiple dynamic views, which is more flexible than being restricted to a single static view of the data. For large volumetric datasets, we maintain interactivity during the transfer function design via intelligent sampling and scalable clustering. Using examples in combustion and climate simulations, we demonstrate how our framework can be used to visualize interesting structures in the volumetric space.

关键词： Transfer functions

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Automatic High-Frequency Click Detection Algorithm for Cetaceans

Automatic High-Frequency Click Detection Algorithm for Cetac...

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International symposium on Underwater Technology

作者： Meng-Fan Tsai Shu-Chun Chuang Shih-Hsien Weng Yin-Ying Fang Wei-Chun Hu Chi-Fang Chen Department of Engineering Science and Ocean Engineering National Taiwan University Taipei Taiwan R.O.C. Engineering department Oceansound CO. LTD. Taipei Taiwan R.O.C. Ship and Ocean Technology Research Center National Taiwan University Taipei Taiwan R.O.C.

ISBN: (数字)9798331534189

ISBN: (纸本)9798331534196

The expansion of offshore wind power facilities in Taiwan's western waters poses significant threats to marine cetaceans, particularly the finless porpoise (Neophocaena phocaenoides sunameri), which is the most frequently stranded cetacean in the region. Causes of stranding include fishery bycatch, environmental changes, vessel collisions, and marine engineering activities. Traditional visual surveys are ineffective for monitoring this species due to its lack of a prominent dorsal fin, limiting the collection of ecological data and the development of conservation strategies. To overcome these challenges, we developed an automated detection algorithm for high-frequency (HF) cetacean clicks using underwater passive acoustic monitoring (PAM). The first algorithm utilized a time-domain computational approach, applying a high-pass filter (>110 kHz) and a peak detection algorithm to identify click trains, incorporating the Peak Energy Algorithm (Step A). The second algorithm introduced a band-pass filter (60–192 kHz) and combined Step A with a Signal-to-Noise Ratio (SNR) calculation (Step B). Additionally, two filters were integrated into the algorithm, informed by studies conducted in the Bohai Sea, Zhangzhou, and Hainan, China, to refine click event detection. analysis of 7.5 hours of acoustic data from the Yun-Chang Rise validated the algorithm. The first algorithm achieved a precision ratio (PR) of 78.09% and a false positive ratio (FPR) of 8.06%, with misclassifications attributed to broadband pulses or closely spaced clicks. The second algorithm, incorporating the SNR threshold, improved PR to 96.3% (+17.4%) and reduced FPR to 0.89% (−7.17%). This algorithm enables efficient HF cetacean click detection and can be integrated into firmware for real-time marine operations. It provides a promising solution to the limitations of visual surveys, enhancing acoustic pattern recognition, and supporting improved cetacean monitoring and conservation in Taiwan's waters.

关键词： Surveys Band-pass filters visualization Acoustics Real-time systems Pattern recognition Detection algorithms Monitoring Signal to noise ratio Microprogramming

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Topology-aware Image Compositing using NVLink 6

Topology-aware Image Compositing using NVLink

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6th ieee symposium on large data analysis and visualization (LDAV)

作者： Christensen, Cameron Fogal, Thomas Luehr, Nathan Woolley, Cliff Univ Utah SCI Inst Salt Lake City UT 84112 USA NVIDIA Santa Clara CA USA

ISBN: (纸本)9781509056590

Compositing is a significant factor in distributed visualization performance at scale on high-performance computing (HPC) systems. For applications such as Para VieworVisIt, the common approach is “sort-last” rendering. For this approach, data are split up to be rendered such that each MPI rank has one or more portions of the over-all domain. After rendering its individual piece(s), each rank has one or more partial images that must be composited with the others to form the final image. The common approach for this step is to use a tree-like communication pattern to reduce the rendered images down to a single image to be displayed to the user. A variety of algorithms have been explored to perform this step efficiently in order to achieve interactive rendering on massive systems [7, 3, 8, 4].

关键词： Graphics processing units Libraries Rendering (computer graphics) data visualization Computer architecture Bandwidth Topology data visualisation Computer Architecture COMPOSITE IMAGES Rendering Bandwidth topology Libraries Graphics Processing Unit High Performance Computing images

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Instrumenting Multiphysics Blood Flow Simulation Codes for In Situ visualization and analysis 11

Instrumenting Multiphysics Blood Flow Simulation Codes for I...

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ieee 11th symposium on large data analysis and visualization (LDAV)

作者： Bucaro, Anthony Murphy, Connor Ferrier, Nicola Insley, Joseph Mateevitsi, Victor Papka, Michael E. Rizzi, Silvio Tan, Jifu Northern Illinois Univ De Kalb IL 60115 USA Argonne Natl Lab Argonne IL 60439 USA

ISBN: (纸本)9781665432832

Blood flow simulations have important applications in engineering and medicine, requiring visualization and analysis for both fluid (blood plasma) and solid (cells). Recent advances in blood flow simulations highlight the need of a more efficient analysis of large data sets. Traditionally, analysis is performed after a simulation is completed, and any changes of simulation settings require running the simulation again. With bi-directional in situ analysis we aim to solve this problem by allowing manipulation of simulation parameters in run time. In this project, we describe our early steps toward this goal and present the in situ instrumentation of two coupled codes for blood flow simulation using the SENSEI in situ framework.

关键词： Training Analytical models Solid modeling Fluids Codes Instruments data visualization

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Quantitative Exploration of large Medieval Manuscripts data for the Codicological Research 6

Quantitative Exploration of Large Medieval Manuscripts Data ...

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6th ieee symposium on large data analysis and visualization (LDAV)

作者： Chandna, Swati Rindone, Francesca Dachsbacher, Carsten Stotzka, Rainer Karlsruhe Inst Technol Inst Data Proc & Elect Karlsruhe Germany Karlsruhe Inst Technol Inst Visualizat & Data Anal Karlsruhe Germany

ISBN: (纸本)9781509056590

Quantitative exploration is gaining in importance for the analysis of the digitized medieval manuscripts. While codicologists can collect such massive amounts of heterogeneous datasets digitized in high-resolution, they still lack efficient and intuitive means to explore data and answer domain-specific research questions. A new approach is needed to enable codicologists with the quantitative exploration of large of data. This paper presents a concept of a fully integrated system to enable a quantitative exploration of various layout features and their uncertainties over a large collection of medieval manuscripts. It is composed of three main components: data handling that ingests large amounts of data into a data repository, feature extraction that extracts various layout features of the manuscripts and quantitative exploration for visual analysis. In addition to this, we introduce new visualization approaches, i.e. the superimposition plot and the manuscript montage plot in combination with the parallel coordinate plot to explore structural layout features of 170,000 manuscript pages with more than 2.5 million measurements of these layout features. Our approach supports codicologists to see the overall structure of the manuscript at a single glimpse, explore heterogeneous layout features and convey uncertainties. We demonstrate typical use-case scenarios of our collaborators in codicological research where our system has enabled them to answer domain-specific questions for analysis of the medieval manuscripts data for the first time.

关键词： medieval manuscripts visualization codicology data handling feature extraction parallel coordinate plot quantitative exploration uncertainties knowledge discovery

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Correlating Sub-Phenomena in Performance datainthe Frequency Domain 6

Correlating Sub-Phenomena in Performance Datainthe Frequency...

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6th ieee symposium on large data analysis and visualization (LDAV)

作者： Vierjahn, Tom Hermanns, Marc-Andre Mohr, Bernd Mueller, Matthias S. Kuhlen, Torsten W. Hentschel, Bernd Rhein Westfal TH Aachen Visual Comp Inst Aachen Germany Rhein Westfal TH Aachen Chair High Performance Comp Aachen Germany Julich Supercomp Ctr Julich Germany JARA High Performance Comp Aachen Germany

ISBN: (纸本)9781509056590

Finding and understanding correlated performance behaviour of the individual functions of massively parallel high-performance computing (HPC) applications is a time-consuming task. In this poster, we propose filtered correlation analysis for automatically locating interdependencies in call-path performance profiles. Transforming the data into the frequency domain splits a performance phenomenon into sub-phenomena to be correlated separately. We provide the mathematical framework and an overview over the visualization, and we demonstrate the effectiveness of our technique.

关键词： D.2.8 [Software Engineering]: Metrics/Measurement-Performance measures I.5.4.m [Pattern Recognition]: Applications-Signal processing I.6.9 [Simulation Modeling and visualization]: visualization

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Optimal Viewpoint Finding for Space Time Cube to Explore Spatio-temporal Characteristics of Vehicle Trajectories on Crossroads 7

Optimal Viewpoint Finding for Space Time Cube to Explore Spa...

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ieee 7th symposium on large data analysis and visualization (LDAV)

作者： Itoh, Masahiko Yokoyama, Daisaku Toyoda, Masashi Kitsuregawa, Masaru Univ Tokyo Tokyo Japan Natl Inst Informat & Commun Technol Tokyo Japan Natl Inst Informat Tokyo Japan

ISBN: (纸本)9781538606179

visualization combining space and time in a single display called "space time cube (STC)" is used for visualizing spatio-temporal movement data. An STC enables us to explore not only shapes and positions of vehicle trajectories but also their temporal distributions. However, it is difficult for users to manually find optimal viewpoints for understanding such characteristics of trajectories. In this paper, we propose an optimal viewpoints selection method for visualizing the spatio-temporal characteristics of vehicle trajectories on a large set of crossroads using an STC. For this purpose, we provide an algorithm based on viewpoint entropy weighted by angles of trajectories with a horizontal line as a measure of viewpoint quality on a projected 2D image. We then argue that our method can be adapted to crossroads with different trajectory shapes.

关键词： Trajectory Shape Entropy data visualization Two dimensional displays Three-dimensional displays Big data

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