Abstract
We present a novel bounding volume hierarchy for GPU-accelerated direct volume rendering (DVR) as well as volumetric mesh slicing and inside-outside intersection testing. Our novel octree-based data structure is laid out linearly in memory using space filling Morton curves. As our new data structure results in tightly fitting bounding volumes, boundary markers can be associated with nodes in the hierarchy. These markers can be used to speed up all three use cases that we examine. In addition, our data structure is memory-efficient, reducing memory consumption by up to 75%. Tree depth and memory consumption can be controlled using a parameterized heuristic during construction. This allows for significantly shorter construction times compared to the state of the art. For GPU-accelerated DVR, we achieve performance gain of 8.4times –13times . For 3D printing, we present an efficient conservative slicing method that results in a 3times –25times speedup when using our data structure. Furthermore, we improve volumetric mesh intersection testing speed by 5times –52times .
Highlights
Bounding volume hierarchies (BVHs) and spatial data structures in general are indispensable tools in computer graphics
The OLBVH data structure consists of six arrays containing: 1. primitive indices P[nm] in [0, n p) sorted by Morton code, 2. tree node bounding volumes BV[nn], 3. child node offsets CO[nni + 1] in [0, nn), 4. primitive index offsets PO[nn + 1] in [0, nm], 5. boolean boundary flags BF[nn], 6. per-level node offsets NO[L] in [1, nn], where n p is the number of primitives in M, nm is sum of the numbers of Morton codes per primitive, nn is the number of tree nodes, and nni is the number of internal tree nodes excluding leaves
We have proposed a novel linear BVH construction approach for volumetric meshes, which produces memory efficient trees in a time efficient manner
Summary
Bounding volume hierarchies (BVHs) and spatial data structures in general are indispensable tools in computer graphics. They are used to accelerate a multitude of algorithms, including collision detection, frustum culling, and ray tracing. We examine how construction and traversal performance as well as memory use can be improved by adapting previous GPU-optimized BVHs for volumetric meshes. We demonstrate the performance and memory benefits of using an octree-based BVH instead of a binary tree-based BVH for Direct volume rendering (DVR), plane intersection for cross-section computation or slicing, and inside-outside intersection testing.
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