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Data-driven simulation methods in computer graphics: cloth, tissue and faces

Published: 05 August 2012 Publication History

Abstract

In recent years, various methods have been introduced to exploit pre-recorded data to improve the performance and/or realism of dynamic deformations, but their differences and similarities have not been adequately analyzed or discussed. So far, the proposed methods have been explored mainly in the research context. They have not been adopted by the computer graphics industry.
This course bridges the gap between research labs and industry to present a unifying theory and understanding of data-driven methods for dynamic deformations that may inspire development of novel solutions. It focuses on application of data-driven methods to three areas of computer animation: dynamic deformation of faces, soft volumetric tissue, and cloth. And it describes how to approach these challenges in a data-driven manner, classifies the various methods, and demonstrates how data-driven methods can work in other settings.

Supplementary Material

Part 1 (crs114_1_12.mp4)
Part 2 (crs114_4_12.mp4)

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cover image ACM Conferences
SIGGRAPH '12: ACM SIGGRAPH 2012 Courses
August 2012
1998 pages
ISBN:9781450316781
DOI:10.1145/2343483
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 05 August 2012

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  • (2018)NNWarp: Neural Network-based Nonlinear DeformationIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.2881451(1-1)Online publication date: 2018
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