OLBVH: octree linear bounding volume hierarchy for volumetric meshes

OLBVH: octree linear bounding volume hierarchy for volumetric meshes

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...

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Bibliographic Details
Published in:The Visual computer Vol. 36; no. 10-12; pp. 2327 - 2340
Main Authors: Ströter, Daniel, Mueller-Roemer, Johannes S., Stork, André, Fellner, Dieter W.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-10-2020
Springer Nature B.V
Subjects:
Algorithms
Artificial Intelligence
Computer Graphics
Computer Science
Construction costs
Consumption
Data structures
Digital video recorders
Image Processing and Computer Vision
Octrees
Original Article
Three dimensional printing
Direct volume rendering
Slicing
Bounding volume hierarchy
Volumetric meshes
Intersection detection
GPGPU
Online Access:Get full text
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Summary: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 × .
ISSN:0178-2789
1432-2315
DOI:10.1007/s00371-020-01886-6