Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423113
M. Lanzagorta, L. Rosenblum, Eddy Kuo, R. Rosenberg
In this paper we briefly discuss the state of the art of Virtual Reality as applied to visualization of scientific and technical data sets. We describe the technologies and software for the creation of Virtual Environments. We also give an overview of some of the more significant and successful Virtual Reality applications in the fields of medicine, engineering, chemistry and computational fluid dynamics.
{"title":"Using Virtual Reality to Visualize Scientific, Engineering, and Medical Data","authors":"M. Lanzagorta, L. Rosenblum, Eddy Kuo, R. Rosenberg","doi":"10.1109/DAGSTUHL.1997.1423113","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423113","url":null,"abstract":"In this paper we briefly discuss the state of the art of Virtual Reality as applied to visualization of scientific and technical data sets. We describe the technologies and software for the creation of Virtual Environments. We also give an overview of some of the more significant and successful Virtual Reality applications in the fields of medicine, engineering, chemistry and computational fluid dynamics.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114844452","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423095
James C. Barnes, B. Hamann, K. Joy
In many applications one is concerned with the approximation of functions from a finite set of given data sites with associated function values. We describe a construction of a hierarchy of triangulations which approximate the given data at varying levels of detail. Intermediate triangulations can be associated with a particular level of the hierarchy by considering their approximation errors. This paper presents a new data-dependent triangulation scheme for multi-valued scattered data in the plane. We perform piecewise linear approximation based on data-dependent triangulations. Our scheme preserves edges (discontinuities) that might exist in a given data set by placing vertices close to edges. We start with a coarse, data-dependent triangulation of the convex hull of the given data sites and subdivide triangles until the error of the piecewise linear approximation implied by a triangulation is smaller than some tolerance.
{"title":"An Edge-Preserving, Data-Dependent Triangulation Scheme for Hierarchical Rendering","authors":"James C. Barnes, B. Hamann, K. Joy","doi":"10.1109/DAGSTUHL.1997.1423095","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423095","url":null,"abstract":"In many applications one is concerned with the approximation of functions from a finite set of given data sites with associated function values. We describe a construction of a hierarchy of triangulations which approximate the given data at varying levels of detail. Intermediate triangulations can be associated with a particular level of the hierarchy by considering their approximation errors. This paper presents a new data-dependent triangulation scheme for multi-valued scattered data in the plane. We perform piecewise linear approximation based on data-dependent triangulations. Our scheme preserves edges (discontinuities) that might exist in a given data set by placing vertices close to edges. We start with a coarse, data-dependent triangulation of the convex hull of the given data sites and subdivide triangles until the error of the piecewise linear approximation implied by a triangulation is smaller than some tolerance.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133219129","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423121
S. Parker, Michelle Miller, C. Hansen, Christopher R. Johnson
SCIRun is a problem solving environment that allows the interactive construction, debugging, and steering of large-scale scientific computations. We review related systems and introduce a taxonomy that explores different computational steering solutions. Considering these approaches, we discuss why a tightly integrated problem solving environment, such as SCIRun, simplifies the design and debugging phases of computational science applications and how such an environment aids in the scientific discovery process.
{"title":"Computational Steering and the SCIRun Integrated Problem Solving Environment","authors":"S. Parker, Michelle Miller, C. Hansen, Christopher R. Johnson","doi":"10.1109/DAGSTUHL.1997.1423121","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423121","url":null,"abstract":"SCIRun is a problem solving environment that allows the interactive construction, debugging, and steering of large-scale scientific computations. We review related systems and introduce a taxonomy that explores different computational steering solutions. Considering these approaches, we discuss why a tightly integrated problem solving environment, such as SCIRun, simplifies the design and debugging phases of computational science applications and how such an environment aids in the scientific discovery process.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117079935","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423129
W. Wynn, J. Barnes, B. Hamann, Mark C. Miller
In many applications one is concerned with techniques for visualizing data sets with real-time interaction. One technique for providing real-time performance is through the use of multiresolution techniques. These techniques provide multiple representations of a data set at different levels of detail. The idea is to select a level of detail that can be rendered within the user's time constraints. We discuss a mechanism which renders finer-detailed representations where the data set has a high frequency, and coarser representations where the data set has lower frequency. We present a new technique for storing curvilinear data sets within a quadtree representation and discuss two rendering schemes: an anti-aliasing scheme and a scheme for maintaining a specified frame rate.
{"title":"Multiresolution and Adaptive Rendering Techniques for Structured, Curvilinear Data","authors":"W. Wynn, J. Barnes, B. Hamann, Mark C. Miller","doi":"10.1109/DAGSTUHL.1997.1423129","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423129","url":null,"abstract":"In many applications one is concerned with techniques for visualizing data sets with real-time interaction. One technique for providing real-time performance is through the use of multiresolution techniques. These techniques provide multiple representations of a data set at different levels of detail. The idea is to select a level of detail that can be rendered within the user's time constraints. We discuss a mechanism which renders finer-detailed representations where the data set has a high frequency, and coarser representations where the data set has lower frequency. We present a new technique for storing curvilinear data sets within a quadtree representation and discuss two rendering schemes: an anti-aliasing scheme and a scheme for maintaining a specified frame rate.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"118 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125757277","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423124
Christian Teitzel, M. Hopf, T. Ertl
The ever growing size of data sets resulting from industrial and scientific simulations and measurements have created an enormous need for analysis tools allowing interactive visualization. A promising hierarchical approach in the area of numerical simulation is called sparse grids. We present two major visualization algorithms working directly on the sparse grid representation of the data set. One of them is interactive particle tracing, which continues to be an important utility for evaluating CFD simulations. The other one is volume ray casting, which is of interest in many areas dealing with three-dimensional scalar data. Additionally we have been able to employ texture hardware support for the necessary function interpolation. Hence, we are able to perform volume visualization methods on compressed data sets at interactive frame rates, which is not possible with other methods like wavelets or fractal compression. In particular, we are able to handle sparse grids of level 13, which correspond to regular volumes of 8193^3 voxels.
{"title":"Scientific Visualization on Sparse Grids","authors":"Christian Teitzel, M. Hopf, T. Ertl","doi":"10.1109/DAGSTUHL.1997.1423124","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423124","url":null,"abstract":"The ever growing size of data sets resulting from industrial and scientific simulations and measurements have created an enormous need for analysis tools allowing interactive visualization. A promising hierarchical approach in the area of numerical simulation is called sparse grids. We present two major visualization algorithms working directly on the sparse grid representation of the data set. One of them is interactive particle tracing, which continues to be an important utility for evaluating CFD simulations. The other one is volume ray casting, which is of interest in many areas dealing with three-dimensional scalar data. Additionally we have been able to employ texture hardware support for the necessary function interpolation. Hence, we are able to perform volume visualization methods on compressed data sets at interactive frame rates, which is not possible with other methods like wavelets or fractal compression. In particular, we are able to handle sparse grids of level 13, which correspond to regular volumes of 8193^3 voxels.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124873418","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423127
M. Ward, Kevin J. Theroux
Benchmarking is a method for quantitatively assessing and comparing the performance of systems. We define perceptual benchmarking as a method for assessing the performance of humans in solving perceptual tasks, and in this paper we describe our research to develop benchmarks for evaluating different multivariate visualization methods under different data and task characteristics.
{"title":"Perceptual Benchmarking for Multivariate Data Visualization","authors":"M. Ward, Kevin J. Theroux","doi":"10.1109/DAGSTUHL.1997.1423127","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423127","url":null,"abstract":"Benchmarking is a method for quantitatively assessing and comparing the performance of systems. We define perceptual benchmarking as a method for assessing the performance of humans in solving perceptual tasks, and in this paper we describe our research to develop benchmarks for evaluating different multivariate visualization methods under different data and task characteristics.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128537362","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423100
Peter Dannenmann, Christof Nuber, R. Küke, N. Schielow, H. Hagen
System development life cycles have been shortened within the last years using enhanced computer-based tools. Each life cycle of a system has been separated from later cycles of other systems except for the common knowledge of developers involved in different phases. To enhance the process of developing and bringing a product to the market from scratch we integrate available tools and information into a single development environment which improves the performance of the complete development team. We will show in this paper how VR- and simulation- tools can be combined to improve the development process of a product. In doing this we will especially focus on the reuse of knowledge gathered in previous phases of the development cycle or even gathered in former projects. The use of virtual reality tools for visualization and interaction in different phases is discussed. Finally we present an approach that is currently under development at DaimlerChrysler Aerospace Space-Infrastructure Division.
{"title":"An Integrated VR- and Simulation-Environment for Supporting the Complete Product Life Cycle of Space-Related Systems","authors":"Peter Dannenmann, Christof Nuber, R. Küke, N. Schielow, H. Hagen","doi":"10.1109/DAGSTUHL.1997.1423100","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423100","url":null,"abstract":"System development life cycles have been shortened within the last years using enhanced computer-based tools. Each life cycle of a system has been separated from later cycles of other systems except for the common knowledge of developers involved in different phases. To enhance the process of developing and bringing a product to the market from scratch we integrate available tools and information into a single development environment which improves the performance of the complete development team. We will show in this paper how VR- and simulation- tools can be combined to improve the development process of a product. In doing this we will especially focus on the reuse of knowledge gathered in previous phases of the development cycle or even gathered in former projects. The use of virtual reality tools for visualization and interaction in different phases is discussed. Finally we present an approach that is currently under development at DaimlerChrysler Aerospace Space-Infrastructure Division.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125149736","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423122
I. Sadarjoen, F. Post
This paper presents a technique for local surface extraction from scalar and vector fields using deformable surfaces. The goal of surface extraction is often to find features, or meaningful patterns in large datasets. To accomplish this, there is a wide spectrum of techniques. On one end of the spectrum, there are purely symbolic techniques, which may use abstract, iconic representations of features. On the other end of the spectrum, there are purely geometric techniques, such as iso-surfaces, which represent features in a naturalistic way, with a wealth of geometric details. Our technique lies in between, since it may represent as many geometric details as the user desires, or give a simplified representation with little computational effort. Using deformable surfaces consists of several steps. First, a region of interest is selected using selection criteria, and an initial surface is placed in the selected region. Then, the surface is gradually deformed by displacing its nodes according to local deformation criteria. Depending on the criteria specified, this deformation process can result in very different types of surfaces. The versatility of the technique is illustrated by two applications: extraction of recirculation zones and vortex tubes from flow fields.
{"title":"Techniques and Applications of Deformable Surfaces","authors":"I. Sadarjoen, F. Post","doi":"10.1109/DAGSTUHL.1997.1423122","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423122","url":null,"abstract":"This paper presents a technique for local surface extraction from scalar and vector fields using deformable surfaces. The goal of surface extraction is often to find features, or meaningful patterns in large datasets. To accomplish this, there is a wide spectrum of techniques. On one end of the spectrum, there are purely symbolic techniques, which may use abstract, iconic representations of features. On the other end of the spectrum, there are purely geometric techniques, such as iso-surfaces, which represent features in a naturalistic way, with a wealth of geometric details. Our technique lies in between, since it may represent as many geometric details as the user desires, or give a simplified representation with little computational effort. Using deformable surfaces consists of several steps. First, a region of interest is selected using selection criteria, and an initial surface is placed in the selected region. Then, the surface is gradually deformed by displacing its nodes according to local deformation criteria. Depending on the criteria specified, this deformation process can result in very different types of surfaces. The versatility of the technique is illustrated by two applications: extraction of recirculation zones and vortex tubes from flow fields.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133158055","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423120
G. Nielson, R. Franke
An algorithm for computing a representation for sub-volumes that segment space into different classifications is given. The starting point is a tetrahedrization of a set of scattered points in space, each with a classification associated with it. The algorithm then marches from tetrahedron to tetrahedron to generate the representation in terms of sub-tetrahedra. The algorithm is very simple and independent of the number of the number of different classifications of points.
{"title":"Computing Segmented Volumes","authors":"G. Nielson, R. Franke","doi":"10.1109/DAGSTUHL.1997.1423120","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423120","url":null,"abstract":"An algorithm for computing a representation for sub-volumes that segment space into different classifications is given. The starting point is a tetrahedrization of a set of scattered points in space, each with a classification associated with it. The algorithm then marches from tetrahedron to tetrahedron to generate the representation in terms of sub-tetrahedra. The algorithm is very simple and independent of the number of the number of different classifications of points.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134333493","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}
Pub Date : 1997-06-09DOI: 10.1109/DAGSTUHL.1997.1423097
Georges-Pierre Bonneau
This paper gives an introduction to wavelet techniques in the context of Scientific Visualization. Wavelets are a powerful tool for the representation of large and complex data sets. Some restrictions apply on the type of data sets which can be represented by wavelets. These restrictions are described in a first part. Thereafter, the basic concepts of wavelet representations are explained: level of detail spaces, wavelet spaces, decomposition and reconstruction algorithms. Orthogonality properties of wavelets and their relations with the ability of computing best approximations are the subject of the next part. Usual applications of wavelet representations in Scientific Visualization are then reviewed. These include progressive transmission, LOD visualization, local area zooming. The last part is dedicated to a recent generalization of wavelet techniques that deals with some types of data sets that cannot be tackle by usual wavelet representations due to the restrictions described in the first part.
{"title":"An Introduction to Wavelets for Scientific Visualization","authors":"Georges-Pierre Bonneau","doi":"10.1109/DAGSTUHL.1997.1423097","DOIUrl":"https://doi.org/10.1109/DAGSTUHL.1997.1423097","url":null,"abstract":"This paper gives an introduction to wavelet techniques in the context of Scientific Visualization. Wavelets are a powerful tool for the representation of large and complex data sets. Some restrictions apply on the type of data sets which can be represented by wavelets. These restrictions are described in a first part. Thereafter, the basic concepts of wavelet representations are explained: level of detail spaces, wavelet spaces, decomposition and reconstruction algorithms. Orthogonality properties of wavelets and their relations with the ability of computing best approximations are the subject of the next part. Usual applications of wavelet representations in Scientific Visualization are then reviewed. These include progressive transmission, LOD visualization, local area zooming. The last part is dedicated to a recent generalization of wavelet techniques that deals with some types of data sets that cannot be tackle by usual wavelet representations due to the restrictions described in the first part.","PeriodicalId":268314,"journal":{"name":"Scientific Visualization Conference (dagstuhl '97)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128003981","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}
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