Fast and scalable point cloud indexing

I’m pleased to announce that our paper with the title “A system for fast and scalable point cloud indexing using task parallelism” has been accepted for presentation at the international conference on Smart Tools and Applications in Graphics (STAG). The conference will take place from 12 to 13 November 2020. It will be held fully online. Admission is complimentary, so feel free to register and listen to our talk!

In our paper, 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.

We’re looking forward to meeting you at the virtual conference!


Bormann, P., & Krämer, M. (2020). A system for fast and scalable point cloud indexing using task parallelism. In S. Biasotti, R. Pintus, & S. Berretti (Eds.), Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference, 153–162.
[ | PDF ]


The Eurographics license agreement allows us to share the final version of the paper here.

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Posted by Michel Krämer
on 5 November 2020

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