A System for Fast and Scalable Point Cloud Indexing Using Task Parallelism

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Date
2020
Authors
Bormann, Pascal
Krämer, Michel
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
We introduce a system for fast, scalable indexing of arbitrarily sized point clouds based on a task-parallel computation model. Points are sorted using Morton indices in order to efficiently distribute sets of related points onto multiple concurrent indexing tasks. To achieve a high degree of parallelism, a hybrid top-down, bottom-up processing strategy is used. Our system achieves a 2.3x to 9x speedup over existing point cloud indexing systems while retaining comparable visual quality of the resulting acceleration structures. It is also fully compatible with widely used data formats in the context of web-based point cloud visualization. We demonstrate the effectiveness of our system in two experiments, evaluating scalability and general performance while processing datasets of up to 52.5 billion points.
Description

        
@inproceedings{
10.2312:stag.20201250
,
booktitle = {
Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference
},
editor = {
Biasotti, Silvia and Pintus, Ruggero and Berretti, Stefano
},
title = {{
A System for Fast and Scalable Point Cloud Indexing Using Task Parallelism
}},
author = {
Bormann, Pascal
 and 
Krämer, Michel
},
year = {
2020
},
publisher = {
The Eurographics Association
},
ISSN = {
2617-4855
},
ISBN = {
978-3-03868-124-3
},
DOI = {
10.2312/stag.20201250
}
}
Citation
URI
https://doi.org/10.2312/stag.20201250
 https://diglib.eg.org:443/handle/10.2312/stag20201250
Collections
Italian Chapter Conference 2020 - Smart Tools and Apps in computer Graphics