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QSplat: a multiresolution point rendering system for large meshes

Open access
Rusinkiewicz, Szymon, Levoy, Marc·2000·Proceedings of the 27th annual conference on Computer graphics and interactive techniques - SIGGRAPH '00

Abstract

Advances in 3D scanning technologies have enabled the practical creation of meshes with hundreds of millions of polygons. Traditional algorithms for display, simplification, and progressive transmission of meshes are impractical for data sets of this size. We describe a system for representing and progressively displaying these meshes that combines a multiresolution hierarchy based on bounding spheres with a rendering system based on points. A single data structure is used for view frustum culling, backface culling, level-of-detail selection, and rendering. The representation is compact and can be computed quickly, making it suitable for large data sets. Our implementation, written for use in a large-scale 3D digitization project, launches quickly, maintains a user-settable interactive frame rate regardless of object complexity or camera position, yields reasonable image quality during motion, and refines progressively when idle to a high final image quality. We have demonstrated the system on scanned models containing hundreds of millions of samples.

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Metadata

Authors
Rusinkiewicz, S., & Levoy, M.
Venue
Proceedings of the 27th annual conference on Computer graphics and interactive techniques - SIGGRAPH '00
Publisher
ACM Press
Published
2000
Pages
343-352
OpenAlex
W2113634802
Cited by
969
References
1
FWCI
25.82
Type
conference paper
Language
en
Open access
bronze

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CoChat. (2026). Citation check: QSplat: a multiresolution point rendering system for large meshes. https://app.cochat.ai/papers/10.1145/344779.344940
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Rusinkiewicz, S., & Levoy, M. (2000). QSplat: a multiresolution point rendering system for large meshes. Proceedings of the 27th annual conference on Computer graphics and interactive techniques - SIGGRAPH '00. https://doi.org/10.1145/344779.344940

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.