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OLBVH: octree linear bounding volume hierarchy for volumetric meshes

Ströter, Daniel and Mueller-Roemer, Johannes S. and Stork, André and Fellner, Dieter W. (2020):
OLBVH: octree linear bounding volume hierarchy for volumetric meshes.
In: The Visual Computer, Springer Link, ISSN 0178-2789,
DOI: 10.1007/s00371-020-01886-6,
[Article]

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 8.4×–13×. For 3D printing, we present an efficient conservative slicing method that results in a 3×–25× speedup when using our data structure. Furthermore, we improve volumetric mesh intersection testing speed by 5×–52×.

Item Type: Article
Erschienen: 2020
Creators: Ströter, Daniel and Mueller-Roemer, Johannes S. and Stork, André and Fellner, Dieter W.
Title: OLBVH: octree linear bounding volume hierarchy for volumetric meshes
Language: English
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 8.4×–13×. For 3D printing, we present an efficient conservative slicing method that results in a 3×–25× speedup when using our data structure. Furthermore, we improve volumetric mesh intersection testing speed by 5×–52×.

Journal or Publication Title: The Visual Computer
Publisher: Springer Link
Uncontrolled Keywords: General Purpose Computation on Graphics Processing Unit (GPGPU), Volume rendering, Hierarchical bounding volumes, Hierarchical data structures
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 15 Jul 2020 07:29
DOI: 10.1007/s00371-020-01886-6
Official URL: https://doi.org/10.1007/s00371-020-01886-6
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