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Constraint-Based motion optimization using a statistical dynamic model (2007)
| Venue: | ACM Trans. Graph |
| Citations: | 34 - 5 self |
BibTeX
@ARTICLE{Chai07constraint-basedmotion,
author = {Jinxiang Chai and Jessica K. Hodgins},
title = {Constraint-Based motion optimization using a statistical dynamic model},
journal = {ACM Trans. Graph},
year = {2007}
}
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Abstract
Figure 1: Motions computed from spatial-temporal constraints. In this paper, we present a technique for generating animation from a variety of user-defined constraints. We pose constraint-based motion synthesis as a maximum a posterior (MAP) problem and develop an optimization framework that generates natural motion satisfying user constraints. The system automatically learns a statistical dynamic model from motion capture data and then enforces it as a motion prior. This motion prior, together with user-defined constraints, comprises a trajectory optimization problem. Solving this problem in the low-dimensional space yields optimal natural motion that achieves the goals specified by the user. We demonstrate the effectiveness of this approach by generating whole-body and facial motion from a variety of spatial-temporal constraints.
