Residency Octree: A Hybrid Approach for Scalable Web-Based Multi-Volume Rendering
Lukas Herzberger, Markus Hadwiger, Robert Krüger, Peter K. Sorger, Hanspeter Pfister, Eduard Gröller, Johanna Beyer
Abstract
We present a hybrid multi-volume rendering approach based on a novel Residency Octree that combines the advantages of out-of-core volume rendering using page tables with those of standard octrees. Octree approaches work by performing hierarchical tree traversal. However, in octree volume rendering, tree traversal and the selection of data resolution are intrinsically coupled. This makes fine-grained empty-space skipping costly. Page tables, on the other hand, allow access to any cached brick from any resolution. However, they do not offer a clear and efficient strategy for substituting missing high-resolution data with lower-resolution data. We enable flexible mixed-resolution out-of-core multi-volume rendering by decoupling the cache residency of multi-resolution data from a resolution-independent spatial subdivision determined by the tree. Instead of one-to-one node-to-brick correspondences, each residency octree node is mapped to a set of bricks from different resolution levels. This makes it possible to efficiently and adaptively choose and mix resolutions, adapt sampling rates, and compensate for cache misses. At the same time, residency octrees support fine-grained empty-space skipping, independent of the data subdivision used for caching. Finally, to facilitate collaboration and outreach, and to eliminate local data storage, our implementation is a web-based, pure client-side renderer using WebGPU and WebAssembly. Our method is faster than prior approaches and efficient for many data channels with a flexible and adaptive choice of data resolution.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 5ebc26e9-f6a2-4c99-a6e5-e4fe890273ceCited by top-tier papers2
- Cell2Cell: Explorative Cell Interaction Analysis in Multi-Volumetric Tissue DataEric Mörth, Kevin Sidak, Zoltan Maliga, Torsten Möller et al.IEEE VIS 2024 · 7 citations
- GL2GPU: Accelerating WebGL Applications via Dynamic API Translation to WebGPUYudong Han, Weichen Bi, Ruibo An, Deyu Tian et al.WWW 2025 · 3 citations
Builds on1
Related papers
- Fast Compressed Segmentation Volumes for Scientific VisualizationMax Piochowiak, Carsten DachsbacherIEEE VIS 2023 · 3 citations
- Ray Tracing Structured AMR Data Using ExaBricksIngo Wald, Stefan Zellmann, Will Usher, Nate Morrical et al.IEEE VIS 2020 · 18 citations
- Mixture of volumetric primitives for efficient neural renderingStephen Lombardi, Tomas Simon, Gabriel Schwartz, Michael Zollhöfer et al.SIGGRAPH 2021 · 240 citations
- UltraMeshRenderer: Efficient Structure and Management of GPU Out-of-core Memory for Real-time Rendering of Gigantic 3D MeshesHuadong Zhang, Lizhou Cao, Chao PengSIGGRAPH 2025 · 2 citations
- GROOT: a real-time streaming system of high-fidelity volumetric videosKyungjin Lee, Juheon Yi, Youngki Lee, Sunghyun Choi et al.MobiCom 2020 · 114 citations
