I.3.7 Three-Dimensional Graphics and Realism
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Institute
Multi-scale phenomena are abundant in many application fields. Representing and numerically simulating such processes is a challenging task since quite different scales have to be resolved, which often requires enormous amounts of storage and computational power. An important strategy in this context is adaptivity, i.e. local adjustment of the spatio-temporal resolution to the details to be resolved. A standard representation therefore are hierarchical, locally refined grids. A specific adaptive approach for solving partial differential equations, usually called AMR (Adaptive Mesh Refinement), was introduced in 1984. The basic idea is to combine the simplicity of structured grids and the advantages of local refinement. In this numerical scheme the computations are started on a set of coarse, potentially overlapping structured grids, that cover the computational domain. Local error criteria are applied to detect regions that require higher resolution. These are covered by subgrids with decreasing mesh spacing, which do not replace, but rather overlap the refined regions of the coarser patches. The equations are advanced on the finer subgrids and the refinement procedure recursively continues until all cells fulfill the considered error criteria, giving rise to a hierarchy of nested levels of refinement. In 1989 a variant of this scheme, called Structured Adaptive Mesh Refinement (SAMR), which reduces some of the complexity of the original approach, was proposed. While the separate subgrids in the AMR scheme could be rotated against each other, in SAMR they are aligned with the major axes of the coordinate system, which for example simplifies the computation of fluxes of (conserved) quantities through the cell faces. SAMR has become more and more popular in the last decade, and nowadays it is applied in many domains like hydrodynamics, meteorology and in particular in cosmology and relativistic astrophysics. Due to this growing popularity, an increasing number of scientists is in need of appropriate interactive visualization techniques to interpret and analyze AMR simulation data. Tools for both, 2D analysis to quantitatively convey the information within single slices and 3D representations to apprehend the overall structure are required. In this thesis we develop direct and indirect volume visualization algorithms for scalar fields that are defined on structured Adaptive Mesh Refinement (SAMR) grids. In particular algorithms for planar slicing and the display of height fields, C0-continuous isosurface extraction, software-, and hardware-based direct volume rendering and temporal interpolation for cell-, and vertex-centered data on unrestricted SAMR grids are proposed. Additionally we investigate the applicability of SAMR data structures for accelerated software-, and hardware-based volume rendering of large 3D scalar data.
Analysis of phenomena that simultaneously occur on quite different spatial and temporal scales require adaptive, hierarchical schemes to reduce computational and storage demands. For data represented as grid functions, the key are adaptive, hierarchical, time-dependent grids that resolve spatio-temporal details without too much redundancy. Here, so-called AMR grids gain increasing popularity. For visualization and feature identification/tracking, the underlying continuous function has to be faithfully reconstructed by spatial and temporal interpolation. Well designed interpolation methods yield better results and help to reduce the amount of data to be stored. We address the problem of temporal interpolation of AMR grid data, e.g.\ for creation of smooth animations or feature tracking. Intermediate grid hierarchies are generated by merging the cells on all refinement levels that are present in the key frames considered. Utilizing a clustering algorithm a structure of nested grids is induced on the resulting collection of cells. The grid functions are mapped to the intermediate hierarchy, thus allowing application of appropriate interpolation techniques.
Tensor Splats
(2003)
An improved general-purpose technique for the visualization of symmetric positive definite tensor fields of rank two is described. It is based on a splatting technique that is built from tiny transparent glyph primitives which are capable to incorporate the full directional information content of a tensor. The result is an information-rich image that allows to read off the preferred directions in a tensor field at each point of a three-dimensional volume or two-dimensional surface. It is useful for analyzing slices or volumes of a three-dimensional tensor field and can be overlayed with standard volume rendering or color mapping. The application of the rendering technique is demonstrated on general relativistic data and the diffusion tensor field of a human brain.
Polygonale Schädelmodelle bilden ein wichtiges Hilfsmittel für computergestützte Planungen im Bereich der plastischen Chirurgie. Wir beschreiben, wie derartige Modelle automatisch aus hochaufgelösten CT-Datensätzen erzeugt werden können. Durch einen lokal steuerbaren Simplifizierungsalgorithmus werden die Modelle so weit vereinfacht, daß auch auf kleineren Graphikcomputern interaktives Arbeiten möglich wird. Die Verwendung eines speziellen Transparenzmodells ermöglicht den ungehinderten Blick auf die bei der Planung relevanten Knochenstrukturen und läßt den Benutzer zugleich die Kopfumrisse des Patienten erkennen.