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作者： Park, Sung W. Linsen, Lars Kreylos, Oliver Owens, John D. Hamann, Bernd IEEE Department of Computer Science University of California Davis CA 95616 Department of Mathematics and Computer Science Ernst-Maritz-Arndt-Universität Greifswald D-17487 Greifswald Germany University of California Davis Department of Mathematics and Computer Science Emst-Moritz-Amdt-Universität Greifswald Germany Department of Electrical and Computer Engineering University of California Davis Davis Institute of Data Analysis and Visualization University of California Davis Department of Computer Science

Natural neighbor interpolation methods, such as Sibson's method, are well-known schemes for multivariate data fitting and reconstruction. Despite its many desirable properties, Sibson's method is computationally expensive and difficult to implement, especially when applied to higher-dimensional data. The main reason for both problems is the method's implementation based on a Voronol diagram of all data points. We describe a discrete approach to evaluating Sibson's interpolant on a regular grid, based solely on finding nearest neighbors and rendering and blending d-dimensional spheres. Our approach does not require us to construct an explicit Voronoi diagram, is easily implemented using commodity three-dimensional graphics hardware, leads to a significant speed increase compared to traditional approaches, and generalizes easily to higher dimensions. For large scattered data sets, we achieve two dimensional (2D) interpolation at interactive rates and 3D interpolation (3D) with computation times of a few seconds. © 2006 IEEE.

关键词： Interpolation

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PointCloudXplore: A visualization Tool for 3D Gene Expression data 1

PointCloudXplore: A Visualization Tool for 3D Gene Expressio...

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1st Workshop of the DFG's International Research Training Group "visualization of Large and Unstructured data Sets - Applications in Geospatial Planning, Modeling, and Engineering"

作者： Rübel, Oliver Weber, Gunther H. Keränen, Soile V. E. Fowlkes, Charless C. Hendriks, Cris L. Luengo Simirenko, Lisa Shah, Nameeta Y. Eisen, Michael B. Biggin, Mark D. Hagen, Hans Sudar, Damir Malik, Jitendra Knowles, David W. Hamann, Bernd International Research Training Group 'Visualization of Large and Unstructured Data Sets' University of Kaiserslautern Germany Institute for Data Analysis and Visualization University of California DavisCA United States Life Sciences and Genomics Divisions Lawrence Berkeley National Laboratory BerkeleyCA United States Computer Science Division University of California BerkeleyCA United States

ISBN: (纸本)9783885794387

The Berkeley Drosophila Transcription Network Project (BDTNP) has developed a suite of methods that support quantitative, computational analysis of threedimensional (3D) gene expression patterns with cellular resolution in early Drosophila embryos, aiming at a more in-depth understanding of gene regulatory networks. We describe a new tool, called PointCloudXplore (PCX), that supports effective 3D gene expression data exploration. PCX is a visualization tool that uses the established visualization techniques of multiple views, brushing, and linking to support the analysis of high-dimensional datasets that describe many genes' expression. Each of the views in PointCloudXplore shows a different gene expression data property. Brushing is used to select and emphasize data associated with defined subsets of embryo cells within a view. Linking is used to show in additional views the expression data for a group of cells that have first been highlighted as a brush in a single view, allowing further data subset properties to be determined. In PCX, physical views of the data are linked to abstract data displays such as parallel coordinates. Physical views show the spatial relationships between different genes' expression patterns within an embryo. Abstract gene expression data displays on the other hand allow for an analysis of relationships between different genes directly in the gene expression space. We discuss on parallel coordinates as one example abstract data view currently available in PCX. We have developed several extensions to standard parallel coordinates to facilitate brushing and the visualization of 3D gene expression data. © 2006 Gesellschaft für Informatik, Bonn.

关键词： visualization

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PointCloudXplore: Visual analysis of 3D Gene Expression data Using Physical Views and Parallel Coordinates

PointCloudXplore: Visual Analysis of 3D Gene Expression Data...

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8th Joint Eurographics/IEEE VGTC Symposium on visualization, EuroVis 2006

作者： Rübel, O. Weber, G.H. Keränen, S.V.E. Fowlkes, C.C. Hendriks, C.L. Luengo Simirenko, L. Shah, N.Y. Eisen, M.B. Biggin, M.D. Hagen, H. Sudar, D. Malik, J. Knowles, D.W. Hamann, B. International Research Training Group "Visualization of Large and Unstructured Data Sets" University of Kaiserslautern Germany Institute for Data Analysis and Visualization University of California DavisCA United States Life Sciences and Genomics Divisions Lawrence Berkeley National Laboratory CA United States Computer Science Division University of California BerkeleyCA United States

ISBN: (纸本)3905673312

To allow a more rigorous understanding of animal gene regulatory networks, the Berkeley Drosophila Transcription Network Project (BDTNP) has developed a suite of methods that support quantitative, computational analysis of three-dimensional (3D) gene expression patterns with cellular resolution in early Drosophila embryos. Here we report the first components of a visualization tool, PointCloudXplore, that allows the relationships between different gene's expression to be analyzed using the BDTNP's datasets. PointCloudXplore uses the established visualization techniques of multiple views, brushing, and linking to support the analysis of high-dimensional datasets that describe many genes' expression. Each of the views in PointCloudXplore shows a different gene expression data property. Brushing is used to select and emphasize data associated with defined subsets of embryo cells within a view. Linking is used to show in additional views the expression data for a group of cells that have first been highlighted as a brush in a single view, allowing further data subset properties to be determined. In PointCloudXplore, physical views of the data are linked to parallel coordinates. Physical views show the spatial relationships between different genes' expression patterns within the embryo. Parallel coordinates, on the other hand, show only some features of each gene's expression, but allow simultaneous analysis of data for many more genes than would be possible in a physical view. We have developed several extensions to standard parallel coordinates to facilitate brushing the visualization of 3D gene expression data. © The Eurographics Association 2006.

关键词： visualization

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Segmenting Point Sets

Segmenting Point Sets

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International Conference on Shape Modeling and Applications

作者： I. Yamazaki V. Natarajan Zhaojun Bai B. Hamann Department of Computer Science University of California Davis CA USA Institute for Data Analysis and Visualization (IDAV) University of California Davis CA USA

Extracting features from point sets is becoming increasingly important for purposes like model classification, matching, and exploration. We introduce a technique for segmenting a point-sampled surface into distinct features without explicit construction of a mesh or other surface representation. Our approach achieves computational efficiency through a three-phase segmentation process. The first phase of the process uses a topo-logical approach to define features and coarsens the input, resulting in a set of supernodes, each one representing a collection of input points. A graph cut is employed in the second phase to bisect the set of supernodes. Similarity between supernodes is computed as a weighted combination of geodesic distances and connectivity. Repeated application of the graph cut results in a hierarchical segmentation of the point input. In the last phase, a segmentation of the original point set is constructed by refining the segmentation of the supernodes based on their associated feature sizes. We apply our segmentation algorithm on laser-scanned models to evaluate its ability to capture geometric features in complex data sets

关键词： Shape Feature extraction Spectral analysis data analysis data visualization computer science data mining Computational efficiency Geophysics computing Laser beam cutting

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Marching diamonds for unstructured meshes

Marching diamonds for unstructured meshes

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VIS 05: IEEE visualization 2005, Proceedings

作者： Anderson, John C. Bennett, Janine C. Joy, Kenneth I. Institute for Data Analysis and Visualization Computer Science Department University of California Davis

ISBN: (纸本)0780394623

We present a higher-order approach to the extraction of isosurfaces from unstructured meshes. Existing methods use linear interpolation along each mesh edge to find isosurface intersections. In contrast, our method determines intersections by performing barycentric interpolation over diamonds formed by the tetrahedra incident to each edge. Our method produces smoother, more accurate isosurfaces. Additionally, interpolating over diamonds, rather than linearly interpolating edge endpoints, enables us to identify up to two isosurface intersections per edge. This paper details how our new technique extracts isopoints, and presents a simple connection strategy for forming a triangle mesh isosurface. © 2005 IEEE.

关键词： Feature extraction

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Topology-based simplification for feature extraction from 3D scalar fields

Topology-based simplification for feature extraction from 3D...

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VIS 05: IEEE visualization 2005, Proceedings

作者： Gyulassy, Attila Natarajan, Vijay Pascucci, Valerio Bremer, Peer-Timo Hamann, Bernd Institute for Data Analysis and Visualization Dept. of Computer Science University of California Davis Center for Applied Scientific Computing Lawrence Livermore National Laboratory Dept. of Computer Science University of Illinois Urbana Champaign

ISBN: (纸本)0780394623

In this paper, we present a topological approach for simplifying continuous functions defined on volumetric domains. We introduce two atomic operations that remove pairs of critical points of the function and design a combinatorial algorithm that simplifies the Morse-Smale complex by repeated application of these operations. The Morse-Smale complex is a topological data structure that provides a compact representation of gradient flow between critical points of a function. Critical points paired by the Morse-Smale complex identify topological features and their importance. The simplification procedure leaves important critical points untouched, and is therefore useful for extracting desirable features. We also present a visualization of the simplified topology. © 2005 IEEE.

关键词： Feature extraction

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Marching diamonds for unstructured meshes

Marching diamonds for unstructured meshes

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IEEE Conference on visualization

作者： J.C. Anderson J.C. Bennett K.I. Joy Institute for Data Analysis and Visualization Computer Science Department University of California Davis USA

We present a higher-order approach to the extraction of isosurfaces from unstructured meshes. Existing methods use linear interpolation along each mesh edge to find isosurface intersections. In contrast, our method determines intersections by performing barycentric interpolation over diamonds formed by the tetrahedra incident to each edge. Our method produces smoother, more accurate isosurfaces. Additionally, interpolating over diamonds, rather than linearly interpolating edge endpoints. enables us to identify up to two isosurface intersections per edge. This paper details how our new technique extracts isopoints, and presents a simple connection strategy for forming a triangle mesh isosurface.

关键词： Isosurfaces Interpolation data analysis data visualization computer science Aircraft data mining Chromium computer graphics Surface cracks

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Evolutionary morphing

Evolutionary morphing

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VIS 05: IEEE visualization 2005, Proceedings

作者： Wiley, David F. Amenta, Nina Alcantara, Dan A. Ghosh, Deboshmita Kil, Yong J. Delson, Eric Harcourt-Smith, Will Rohlf, F. James John, Katherine St. Hamann, Bernd Institute for Data Analysis and Visualization Department of Computer Science University of California Davis American Museum of Natural History Lehman College City University of New York Department of Ecology and Evolution State University of New York Stony Brook

ISBN: (纸本)0780394623

We introduce a technique to visualize the gradual evolutionary change of the shapes of living things as a morph between known three-dimensional shapes. Given geometric computer models of anatomical shapes for some collection of specimens - here the skulls of the some of the extant members of a family of monkeys - an evolutionary tree for the group implies a hypothesis about the way in which the shape changed through time. We use a statistical model which expresses the value of some continuous variable at an internal point in the tree as a weighted average of the values at the leaves. The framework of geometric morphometrics can then be used to define a shape-space, based on the correspondences of landmark points on the surfaces, within which these weighted averages can be realized as actual surfaces. Our software provides tools for performing and visualizing such an analysis in three dimensions. Beginning with laser range scans of crania, we use our landmark editor to interactively place landmark points on the surface. We use these to compute a "tree-morph" that smoothly interpolates the shapes across the tree. Each intermediate shape in the morph is a linear combination of all of the input surfaces. We create a surface model for an intermediate shape by warping all the input meshes towards the correct shape and then blending them together. To do the blending, we compute a weighted average of their associated trivariate distance functions and then extract a surface from the resulting function. We implement this idea using the squared distance function, rather than the usual signed distance function, in a novel way.

关键词： computer graphics

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Maximizing adaptivity in hierarchical topological models

Maximizing adaptivity in hierarchical topological models

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International Conference on Shape Modeling and Applications

作者： P.-T. Bremer V. Pascucci B. Hamann Department of Computer Science University of Illinois Urbana-Champaign USA Lawrence Livermore National Laboratory Center for Applied Scientific Computing USA Institute for Data Analysis and Visualization Department of Computer Science University of California Davis USA

We present an approach to hierarchically encode the topology of functions over triangulated surfaces. Its Morse-Smale complex, a well known structure in computational topology, describes the topology of a function. Following concepts of Morse theory, a Morse-Smale complex (and therefore a function's topology) can be simplified by successively canceling pairs of critical points. We demonstrate how cancellations can be effectively encoded to produce a highly adaptive topology-based multi-resolution representation of a given function. Contrary to the approach, we avoid encoding the complete complex in a traditional mesh hierarchy. Instead, the information is split into a new structure we call a cancellation forest and a traditional dependency graph. The combination of this new structure with a traditional mesh hierarchy proofs to be significantly more flexible than the one previously reported. In particular, we can create hierarchies that are guaranteed to be of logarithmic height.

关键词： Topology data visualization data analysis computer science Encoding Level set Shape Scientific computing Laboratories Transfer functions

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Guest editorial: Introduction to the special issue on adaptive learning systems in communication networks

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IEEE Transactions on Neural Networks 2005年第5期16卷 1013-1018页

作者： Parlos, Alexander G. Ji, Chuanyi Parisini, Thomas Baglietto, Marco Atiya, Amir F. Claffy, K. Texas A and M University Department of Mechanical Engineering College Station TX 77483 United States Georgia Institute of Technology Department of Electrical and Computer Engineering Atlanta GA 30332 United States University of Trieste Department of Electrical Electronic and Computer Engineering Trieste Italy University of Genova Department of Communications Computer and Systems Science Genova Italy Cairo University Department of Computer Engineering Cairo Egypt University of California Cooperative Association for Internet Data Analysis San Diego Supercomputer Center La Jolla CA 92093 United States

No abstract available

关键词： Adaptive systems Learning systems Intelligent networks Communication networks Fault detection Neural networks Fault diagnosis Web and internet services IP networks Adaptive signal processing

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