Direct Volume Rendering of Tree-based Tetrahedral Adaptive Mesh Refinement Data
Musa Ege Ünalan
Master Student
(Supervisor: Prof.Dr.Uğur Güdükbay) Computer Engineering Department
Bilkent University
Abstract: Ray-tracing-based direct volume rendering (DVR) techniques often use data representations such as regular grids, unstructured meshes, and adaptive mesh refinement (AMR) data. A less-explored option for DVR is tree-based tetrahedral AMR data (Tet-AMR), which combines the benefits of unstructured meshes and AMR by having both a coarse unstructured tetrahedral mesh that can represent complex domains, on which acceleration structures can be constructed to perform efficient ray-triangle intersection tests, and a forest of refinement trees, each rooted at a coarse mesh element, increasing detail where needed. Tet-AMR data can be visualized by converting it to an unstructured mesh representation; however, this approach introduces new unstructured elements, increasing memory usage during rendering while decreasing the performance of acceleration structures. We propose leveraging the regularly subdivided nature of the tetrahedral refinement trees by only storing the coarse geometry during rendering. We construct a bounding volume hierarchy over the coarse mesh to efficiently identify the refinement trees from which to sample. Then, we generate the geometry of the finer level elements on the fly when traversing the refinement trees to find the actual elements to sample. We also show that the tree structure can be utilized to implement a dynamic view-dependent level of detail effect, improving performance by decreasing fidelity in regions that minimally affect the final image. It can be used to obtain a density range for each tree, enabling empty space skipping with ray marching renderers or used as local majorant extinctions with delta tracking renderers to improve performance. Our proposed method outperforms or performs comparably to rendering the Tet-AMR as an unstructured mesh, using less memory and enabling the described effect and optimizations on the various datasets we have tested with our GPU renderers.
DATE: September 12, Friday @ 10:00 Place: EA 409