arrow
返回

Multiresolution Green's function methods for interactive simulation of large-scale elastostatic objects

delete2003-01-01
delete75
PRE
AI
D
Doug L. James
D
Dinesh K. Pai
DOI:10.1145/588272.588278delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
We present a framework for low-latency interactive simulation of linear elastostatic models, and other systems arising from linear elliptic partial differential equations, which makes it feasible to interactively simulate large-scale physical models. The deformation of the models is described using precomputed Green's functions (GFs), and runtime boundary value problems (BVPs) are solved using existing Capacitance Matrix Algorithms (CMAs). Multiresolution techniques are introduced to control the amount of information input and output from the solver thus making it practical to simulate and store very large models. A key component is the efficient compressed representation of the precomputed GFs using second-generation wavelets on surfaces. This aids in reducing the large memory requirement of storing the dense GF matrix, and the fast inverse wavelet transform allows for fast summation methods to be used at run-time for response synthesis. Resulting GF compression factors are directly related to interactive simulation speedup, and examples are provided with hundredfold improvements at modest error levels. We also introduce a multiresolution constraint satisfaction technique formulated as a hierarchical CMA, so named because of its use of hierarchical GFs describing the response due to hierarchical basis constraints. This direct solution approach is suitable for hard real-time simulation since it provides a mechanism for gracefully degrading to coarser resolution constraint approximations. The GFs' multiresolution displacement fields also allow for run-time adaptive multiresolution rendering.
Keyword:
algorithms
capacitance matrix
deformation
elastostatic
fast summation
force feedback
Green's function
interactive real-time applications
lifting scheme
wavelets
real-time
updating
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

ACM Transactions on Graphics 封面图
ACM Transactions on Graphics
IF:
9.5
论文数:
4.7K
被引数:
3.6W

机构

暂无机构信息
引用论文

引用论文

Statistical Literacy of Obstetrics-Gynecology Residents
err2013-06-01
err0
errOAAI
errBritta L. Anderson; Sterling Williams; Jay Schulkin
err分享
err收藏
err分享
err收藏
Real-time PCR
err
IF0
err2007-01-24
err0
PREAI
err
err分享
err收藏
A top-down microsystems design methodology and associated challenges
err2024-09-06
err0
errOAAI
errM.S. McCorquodale; F.H. Gebara; K.L. Kraver; E.D. Marsman; R.M. Senger; R.B. Brown
err分享
err收藏
学者 查看更多内容