Unified many-worlds browsing of arbitrary physics-based animations
Purvi Goel, Doug L. James
Abstract
Manually tuning physics-based animation parameters to explore a simulation outcome space or achieve desired motion outcomes can be notoriously tedious. This problem has motivated many sophisticated and specialized optimization-based methods for fine-grained (keyframe) control, each of which are typically limited to specific animation phenomena, usually complicated, and, unfortunately, not widely used. In this paper, we propose Unified Many-Worlds Browsing (UMWB), a practical method for sample-level control and exploration of physics-based animations. Our approach supports browsing of large simulation ensembles of arbitrary animation phenomena by using a unified volumetric WORLDPACK representation based on spatiotemporally compressed voxel data associated with geometric occupancy and other low-fidelity animation state. Beyond memory reduction, the WORLDPACK representation also enables unified query support for interactive browsing: it provides fast evaluation of approximate spatiotemporal queries, such as occupancy tests that find ensemble samples ("worlds") where material is either IN or NOT IN a user-specified spacetime region. WORLDPACKS also support real-time hardware-accelerated voxel rendering by exploiting the spatially hierarchical and temporal RLE raster data structure. Our UMWB implementation supports interactive browsing (and offline refinement) of ensembles containing thousands of simulation samples, and fast spatiotemporal queries and ranking. We show UMWB results using a wide variety of physics-based animation phenomena---not just JELL-O ® .
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 c1411794-48ef-4dd6-a308-e96ffa2eb52aBuilds on6
- Sequential gallery for interactive visual design optimizationYuki Koyama, Issei Sato, Masataka GotoSIGGRAPH 2020 · 90 citations
- Lagrangian neural style transfer for fluidsByungsoo Kim, Vinicius C. Azevedo, Markus Gross, Barbara SolenthalerSIGGRAPH 2020 · 43 citations
- QuanTaichi: a compiler for quantized simulationsYuanming Hu, Jiafeng Liu, Xuanda Yang, Mingkuan Xu et al.SIGGRAPH 2021 · 40 citations
- Design Adjectives: A Framework for Interactive Model-Guided Exploration of Parameterized Design SpacesEvan Shimizu, Matthew Fisher, Sylvain Paris, James McCann et al.UIST 2020 · 22 citations
- Stream-guided smoke simulationsSyuhei Sato, Yoshinori Dobashi, Theodore KimSIGGRAPH 2021 · 21 citations
Related papers
- SCom DAG: compact representation of spatial data for real-time renderingAlbert Garifullin, Nikolay Mayorov, Eduard Hauer, Alexey G. Voloboy et al.SIGGRAPH 2026
- Attribute-Aware RBFs: Interactive Visualization of Time Series Particle Volumes Using RT Core Range QueriesNate Morrical, Stefan Zellmann, Alper Sahistan, Patrick C. Shriwise et al.IEEE VIS 2023 · 4 citations
- OmniPhysGS: 3D Constitutive Gaussians for General Physics-Based Dynamics GenerationYuchen Lin, Chenguo Lin, Jianjin Xu, Yadong MuICLR 2025
- PIE-NeRF: Physics-Based Interactive Elastodynamics with NeRFYutao Feng, Yintong Shang, Xuan Li, Tianjia Shao et al.CVPR 2024
- Probabilistic Occlusion Culling using Confidence Maps for High-Quality Rendering of Large Particle DataMohamed Ibrahim, Peter Rautek, Guido Reina, Marco Agus et al.IEEE VIS 2021 · 11 citations
