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SciVis 2018 Committees
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/scivis.2018.8823787
{"title":"SciVis 2018 Committees","authors":"","doi":"10.1109/scivis.2018.8823787","DOIUrl":"https://doi.org/10.1109/scivis.2018.8823787","url":null,"abstract":"","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128248105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Color Interpolation for Non-Euclidean Color Spaces 非欧几里德色彩空间的色彩插值
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/SciVis.2018.8823597
Max Zeyen, Tobias Post, H. Hagen, J. Ahrens, D. Rogers, R. Bujack
{"title":"Color Interpolation for Non-Euclidean Color Spaces","authors":"Max Zeyen, Tobias Post, H. Hagen, J. Ahrens, D. Rogers, R. Bujack","doi":"10.1109/SciVis.2018.8823597","DOIUrl":"https://doi.org/10.1109/SciVis.2018.8823597","url":null,"abstract":"Color interpolation is critical to many applications across a variety of domains, like color mapping or image processing. Due to the characteristics of the human visual system, color spaces whose distance measure is designed to mimic perceptual color differences tend to be non-Euclidean. In this setting, a generalization of established interpolation schemes is not trivial. This paper presents an approach to generalize linear interpolation to colors for color spaces equipped with an arbitrary non-Euclidean distance measure. It makes use of the fact that in Euclidean spaces, a straight line coincides with the shortest path between two points. Additionally, we provide an interactive implementation of our method for the CIELAB color space using the CIEDE2000 distance measure integrated into VTK and ParaView.","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130752641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Interactive Visualization and Analysis of High Resolution HPC Simulation Data on a Laptop With VTK 基于VTK的笔记本电脑高分辨率HPC仿真数据交互可视化与分析
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/SciVis.2018.8823596
J. Dubois, Guénolé Harel, Jacques-Bernard Lekien
{"title":"Interactive Visualization and Analysis of High Resolution HPC Simulation Data on a Laptop With VTK","authors":"J. Dubois, Guénolé Harel, Jacques-Bernard Lekien","doi":"10.1109/SciVis.2018.8823596","DOIUrl":"https://doi.org/10.1109/SciVis.2018.8823596","url":null,"abstract":"We present a highly efficient solution to interact with the Deep Water Impact Ensemble Data Set provided for the Scientific Visualization Contest 2018. Interactive visualization is made possible on one core of a laptop with the full resolution and the same accuracy as in the original data set, when originally 256 up to 2048 supercomputer nodes were required to generate the data. As far as we know this is the only way to achieve full-resolution exploration on a laptop. We first expose how our approach allows more efficient visualization by using the Tree-Based Adaptive Mesh Refinement grid data structure we introduced in VTK, vtkHyperTreeGrid [1], as compared to structured or unstructured approaches. Then we elaborate on the visualization capabilities offered by vtkHyperTreeGrid-optimized algorithms and the performance achieved on the limited resources available on a laptop. Next, we present how the hierarchical structure makes possible novel ways of exploring data interactively and helps achieve accelerated data exploration by hierarchically driving decimation of values. Finally, we show preliminary results of interactive volume rendering using splatting.","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126538866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Cluster-Based Visualization for Merger Tree Data: The Challenge of Missing Expectations 基于聚类的合并树数据可视化:缺失预期的挑战
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/SciVis.2018.8823586
A. Preston, K. Ma
{"title":"Cluster-Based Visualization for Merger Tree Data: The Challenge of Missing Expectations","authors":"A. Preston, K. Ma","doi":"10.1109/SciVis.2018.8823586","DOIUrl":"https://doi.org/10.1109/SciVis.2018.8823586","url":null,"abstract":"Scientific simulations are yielding increasing amounts of data; to visualize the full output from a simulation, one must first reduce clutter and obstruction. Clustering algorithms are common tools for condensing information and decreasing clutter when analyzing and visualizing simulation output. Often, simulation data have intuitive groupings. In some cases, though, such as merger trees from N-body dark matter simulations, there are limited expectations for clustering results. We investigate cluster-based visualization design for merger tree data, testing whether multidimensional encodings and opening the \"black box\" can allow for meaningful representation and exploration of these data.","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116519290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
aflak: Pluggable Visual Programming Environment with Quick Feedback Loop Tuned for Multi-Spectral Astrophysical Observations 用于多光谱天体物理观测的快速反馈回路的可插拔可视化编程环境
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/SciVis.2018.8823788
Malik Olivier Boussejra, K. Matsubayashi, Yuriko Takeshima, S. Takekawa, Rikuo Uchiki, M. Uemura, I. Fujishiro
{"title":"aflak: Pluggable Visual Programming Environment with Quick Feedback Loop Tuned for Multi-Spectral Astrophysical Observations","authors":"Malik Olivier Boussejra, K. Matsubayashi, Yuriko Takeshima, S. Takekawa, Rikuo Uchiki, M. Uemura, I. Fujishiro","doi":"10.1109/SciVis.2018.8823788","DOIUrl":"https://doi.org/10.1109/SciVis.2018.8823788","url":null,"abstract":"With the improvements of telescopes and proliferation of sky surveys, there is always more astrophysical data to analyze, but not so many astronomers. We present aflak, a visualization environment to analyze astronomical datasets. This paper’s contribution lies in that we leverage visual programming techniques to conduct fine-grained astronomical transformations, filtering and visual analyses on multi-spectral datasets, with the possibility for astronomers to interactively fine-tune all the interacting parameters. As the visual program is gradually designed, the computed results can be visualized in real time, thus aflak puts the astronomer in the loop, while managing data provenance at the same time.","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134218484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
VRGE: An Immersive Visualization Application for the Geosciences VRGE:用于地球科学的沉浸式可视化应用
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/SciVis.2018.8823763
David Hyde, Tyler R. Hall, J. Caers
{"title":"VRGE: An Immersive Visualization Application for the Geosciences","authors":"David Hyde, Tyler R. Hall, J. Caers","doi":"10.1109/SciVis.2018.8823763","DOIUrl":"https://doi.org/10.1109/SciVis.2018.8823763","url":null,"abstract":"The rapid onset of inexpensive, portable virtual reality (VR) devices has created opportunities for scientific visualization tools that harness this new, immersive modality. Researchers in the geological sciences, in particular those focused on earth resources (energy, water, minerals), are faced with significant challenges in building and understanding increasingly complex geological models. In this paper, we address these joint opportunities by introducing the Virtual Reality Geomodeling Environment (VRGE): a scientific visualization tool leveraging the Oculus Rift VR system, specialized for users involved in geological modeling. VRGE offers a number of features for viewing and interacting with geological models in VR, including human-centric navigation and manipulation, implicit surface editing, visual conditioning, and uncertainty analysis. Moreover, we examine how the design of VRGE meets current needs of the earth resources industry, in the context of reviewing the state-of-the-art, conducting an expert survey, and discussing performance.","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134512935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Ocean Current Segmentation at Different Depths and Correlation with Temperature in a MPAS-Ocean Simulation mpas海洋模拟中不同深度的海流分割及其与温度的相关性
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/SciVis.2018.8823794
Petra Gospodnetić, D. Banesh, P. Wolfram, M. Petersen, H. Hagen, J. Ahrens, M. Rauhut
{"title":"Ocean Current Segmentation at Different Depths and Correlation with Temperature in a MPAS-Ocean Simulation","authors":"Petra Gospodnetić, D. Banesh, P. Wolfram, M. Petersen, H. Hagen, J. Ahrens, M. Rauhut","doi":"10.1109/SciVis.2018.8823794","DOIUrl":"https://doi.org/10.1109/SciVis.2018.8823794","url":null,"abstract":"When analyzing and interpreting results of an ocean simulation, the prevalent method in oceanography is to visualize the complete dataset. However, this can lead to data being missed or misinterpreted due to the distraction caused by the extraneous data of the simulation. Furthermore, when the data stretches over many layers in depth or over numerous time-steps, the ability to track attributes such as ocean currents becomes difficult due to the complexity of the data. We propose an image processing approach to simulation preprocessing for visualization purposes, which offers automation of ocean current tracking within a simulation and ocean current segmentation from the rest of the simulation data. Using the proposed approach, it is possible to automatically identify the most scientifically-relevant streams, extract them from the rest of the simulation and correlate their behavior with other simulation parameters.","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129479641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
SciVis 2018 Short Paper Reviewers SciVis 2018短论文审稿人
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/scivis.2018.8823797
{"title":"SciVis 2018 Short Paper Reviewers","authors":"","doi":"10.1109/scivis.2018.8823797","DOIUrl":"https://doi.org/10.1109/scivis.2018.8823797","url":null,"abstract":"","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129560061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
QuFlow: Visualizing Parameter Flow in Quantum Circuits for Understanding Quantum Computation QuFlow:可视化量子电路中的参数流以理解量子计算
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/SciVis.2018.8823602
Siyuan Lin, Hao Jiang, Ling-yun Sun
{"title":"QuFlow: Visualizing Parameter Flow in Quantum Circuits for Understanding Quantum Computation","authors":"Siyuan Lin, Hao Jiang, Ling-yun Sun","doi":"10.1109/SciVis.2018.8823602","DOIUrl":"https://doi.org/10.1109/SciVis.2018.8823602","url":null,"abstract":"With the rapid progress of quantum computation recently, it attracts a substantial amount of people to learn quantum computation. Quantum computation differs a lot from classical computation. To help novices learn quantum computation, we conducted a interview with people who are learning quantum computation and found that novices feel confused about 1) how quantum gates contribute to the final results in a complicated quantum circuit and 2) how the final results generate steps along the quantum circuits. Thus, we present QuFlow, an interactive visualization tool for teaching the fundamentals of quantum computation. Users can use it to build a quantum circuit, then QuFlow will simulate the quantum circuit in a classical computer. After simulation, QuFlow will not only present the final output results of quantum circuits but also shows how the parameters change along the quantum circuits. A qualitative user study was carried out among target users, and the results suggested that QuFlow could be effective for learning quantum computation.","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131370462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
SciVis 2018 Committee
2018 IEEE Scientific Visualization Conference (SciVis) Pub Date : 2018-10-01 DOI: 10.1109/scivis.2018.8823593
{"title":"SciVis 2018 Committee","authors":"","doi":"10.1109/scivis.2018.8823593","DOIUrl":"https://doi.org/10.1109/scivis.2018.8823593","url":null,"abstract":"","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116201755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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