Near-exhaustive Precomputation of Secondary Cloth Effects
James O'Brien1, Doyub Kim2, Adrien Treuille3, Kayvon Fatahalian4 and Rahul Narain5
The central argument against data-driven methods in computer graphics rests on the curse of dimensionality: it is intractable to precompute “everything” about a complex space. In this paper, we challenge that assumption by using several thousand CPU-hours to perform a massive exploration of the space of secondary clothing effects on a character animated through a large motion graph. Our system continually explores the phase space of cloth dynamics, in- crementally constructing a secondary cloth motion graph that cap- tures the dynamics of the system. We find that it is possible to sample the dynamical space to a low visual error tolerance and that secondary motion graphs containing tens of gigabytes of raw mesh data can be compressed down to only tens of megabytes. These re- sults allow us to capture the effect of high-resolution, off-line cloth simulation for a rich space of character motion and deliver it effi- ciently as part of an interactive application.
2Carnegie Mellon University
3Carnegie Mellon University
4Carnegie Mellon University
More information: http://graphics.berkeley.edu/papers/Kim-NEP-2013-07/