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Cyclic animation using Partial differential Equations
Gonzalez Castro, Gabriela ; Athanasopoulos, Michael ; Ugail, Hassan ; Willis, P. ; Sheng, Y
Gonzalez Castro, Gabriela
Athanasopoulos, Michael
Ugail, Hassan
Willis, P.
Sheng, Y
Publication Date
2010
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(c) 2010 Springer Verlag. Reproduced in accordance with the publisher's self-archiving policy.
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Abstract
This work presents an efficient and fast method for achieving cyclic animation using Partial Differential Equations (PDEs). The boundary-value nature associ- ated with elliptic PDEs offers a fast analytic solution technique for setting up a framework for this type of animation. The surface of a given character is thus cre- ated from a set of pre-determined curves, which are used as boundary conditions so that a number of PDEs can be solved. Two different approaches to cyclic ani- mation are presented here. The first consists of using attaching the set of curves to a skeletal system hold- ing the animation for cyclic motions linked to a set mathematical expressions, the second one exploits the spine associated with the analytic solution of the PDE as a driving mechanism to achieve cyclic animation, which is also manipulated mathematically. The first of these approaches is implemented within a framework related to cyclic motions inherent to human-like char- acters, whereas the spine-based approach is focused on modelling the undulatory movement observed in fish when swimming. The proposed method is fast and ac- curate. Additionally, the animation can be either used in the PDE-based surface representation of the model or transferred to the original mesh model by means of
a point to point map. Thus, the user is offered with the choice of using either of these two animation repre- sentations of the same object, the selection depends on the computing resources such as storage and memory capacity associated with each particular application.
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Citation
Gonzalez Castro G., Athanasopoulos M., Ugail H., Willis P. and Sheng Y. (2010). Cyclic animation using Partial differential Equations. The Visual Computer. Vol. 26, No. 5, pp. 325-338.
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