Tools for Analysis and Visualization of Large Time-Varying CFD Data Sets

In the second year, we continued to built upon and improve our scanline-based direct volume renderer that we developed in the first year of this grant. This extremely general rendering approach can handle regular or irregular grids, including overlapping multiple grids, and polygon mesh surfaces. It runs in parallel on multi-processors. It can also be used in conjunction with a k-d tree hierarchy, where approximate models and error terms are stored in the nodes of the tree, and approximate fast renderings can be created. We have extended our software to handle time-varying data where the data changes but the grid does not. We are now working on extending it to handle more general time-varying data. We have also developed a new extension of our direct volume renderer that uses automatic decimation of the 3D grid, as opposed to an explicit hierarchy. We explored this alternative approach as being more appropriate for very large data sets, where the extra expense of a tree may be unacceptable. We also describe a new approach to direct volume rendering using hardware 3D textures and incorporates lighting effects. Volume rendering using hardware 3D textures is extremely fast, and machines capable of using this technique are becoming more moderately priced. While this technique, at present, is limited to use with regular grids, we are pursuing possible algorithms extending the approach to more general grid types. We have also begun to explore a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH '96. In our initial implementation, we automatically image the volume from 32 equi-distant positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation. We are studying whether this will give a quantitative measure of the effects of approximation. We have created new tools for exploring the differences between images produced by various rendering methods. Images created by our software can be stored in the SGI RGB format. Our idtools software reads in pair of images and compares them using various metrics. The differences of the images using the RGB, HSV, and HSL color models can be calculated and shown. We can also calculate the auto-correlation function and the Fourier transform of the image and image differences. We will explore how these image differences compare in order to find useful metrics for quantifying the success of various visualization approaches. In general, progress was consistent with our research plan for the second year of the grant

An Isosurface Continuity Algorithm for Super Adaptive Resolution Data

We present the chain-gang algorithm for isosurface rendering of super adaptive resolution (SAR) volume data in order to minimize (1) the space needed for storage of both the data and the isosurface and (2) the time taken for computation. The chain-gan

Speech Communication

Contains table of contents for Part V, table of contents for Section 1, reports on six research projects and a list of publications.C.J. Lebel FellowshipDennis Klatt Memorial FundNational Institutes of Health Grant R01-DC00075National Institutes of Health Grant R01-DC01291National Institutes of Health Grant R01-DC01925National Institutes of Health Grant R01-DC02125National Institutes of Health Grant R01-DC02978National Institutes of Health Grant R01-DC03007National Institutes of Health Grant R29-DC02525National Institutes of Health Grant F32-DC00194National Institutes of Health Grant F32-DC00205National Institutes of Health Grant T32-DC00038National Science Foundation Grant IRI 89-05249National Science Foundation Grant IRI 93-14967National Science Foundation Grant INT 94-2114

Modeling Animals with Bones, Muscles, and Skin

A new approach to animal modeling and animation using simulated individual bones and muscles, soft tissues, and skin is described. Bones and muscles (made of combinations of ellipsoids) can be generated automatically from a tree structure and joint geometry or designed interactively. Together with soft tissue, these provide the underlying anatomy. A polygonal skin mesh is automatically generated to form a smooth covering. Muscles stretch across joints, and their orientations, sizes, and shapes change during joint motion. The skin mesh automatically adjusts to changes in position due to the effect of neighboring skin points and anchor points associated with the underlying anatomy. Much of the process is automated; parameters may be be adjusted, and components can be added and removed. Manipulation and animation occur at comfortable interactive speeds on graphics workstations. Keywords: computer graphics, computer animation, computer modeling, animal and skin modeling. 1 Introduction ..

Multi-dimensional trees for controlled volume rendering and compression

This paper explores the use of multi-dimensional trees to provide spatial and temporal efficiencies in imaging large data sets. Each node of the tree contains a model of the data in terms of a fixed number of basis functions, a measure of the error in that model, and a measure of the importance of the data in the region covered by the node. A divide-andconquer algorithm permits efficient computation of these quantities at all nodes of the tree. The flexible design permits various sets of basis functions, error criteria, and importance criteria to be implemented easily. Selective traversal of the tree provides images in acceptable time, by drawing nodes that cover a large volume as single objects when the approximation error and/or importance are low, and descending to finer detail otherwise. Trees over very large datasets can be pruned by the same criterion to provide data representations of acceptable size and accuracy. Compression and traversal are controlled by a user-defined combination of modeling error and data importance. For imaging decisions, additional parameters are considered, including grid location, allowed time, and projected screen area. To analyze results, two evaluation metrics are used: the first compares the hierarchical model to actual data values, and the second compares the pixel values of images produced by different parameter settings

"Tools For Analysis and Visualization of Large Time- Varying CFD Data Sets"

During the four years of this grant (including the one year extension), we have explored many aspects of the visualization of large CFD (Computational Fluid Dynamics) datasets. These have included new direct volume rendering approaches, hierarchical methods, volume decimation, error metrics, parallelization, hardware texture mapping, and methods for analyzing and comparing images. First, we implemented an extremely general direct volume rendering approach that can be used to render rectilinear, curvilinear, or tetrahedral grids, including overlapping multiple zone grids, and time-varying grids. Next, we developed techniques for associating the sample data with a k-d tree, a simple hierarchial data model to approximate samples in the regions covered by each node of the tree, and an error metric for the accuracy of the model. We also explored a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH (Association for Computing Machinery Special Interest Group on Computer Graphics) '96. In our initial implementation, we automatically image the volume from 32 approximately evenly distributed positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation

Anatomically Based Modeling

We describe an improved, anatomically based approach to modeling and animating animals. Underlying muscles, bones, and generalized tissue are modeled as triangle meshes or ellipsoids. Muscles are deformable discretized cylinders lying between fixed origins and insertions on specific bones. Default rest muscle shapes can be used, or the rest muscle shape can be designed by the user with a small set of parameters. Muscles automatically change shape as the joints move. Skin is generated by voxelizing the underlying components, filtering, and extracting a polygonal isosurface. Isosurface skin vertices are associated with underlying components and move with them during joint motion. Skin motion is consistent with an elastic membrane model. All components are parameterized and can be reused on similar bodies with non-uniformly scaled parts. This parameterization allows a non-uniformly sampled skin to be extracted, maintaining more details at the head and extremities. CR Categories and Subje..