A cellular neural network based deformable model
This paper presents a new methodology for the deformation of soft objects by drawing an analogy between cellular neural network and elastic deformation. An improved cellular neural network model is developed to simulate the deformation of soft objects. The cellular neural network model incorporates...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Springer Verlag
2006
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/17214 |
| Summary: | This paper presents a new methodology for the deformation of soft objects by drawing an analogy between cellular neural network and elastic deformation. An improved cellular neural network model is developed to simulate the deformation of soft objects. The cellular neural network model incorporates the internal elastic forces and the external force to model the deformation dynamics. A finite volume based method is presented to derive the discrete differential operators over irregular nets for obtaining the internal elastic forces. The finite volume method enforces the conservation of energy in a discrete sense and provides an intuitively geometric discretization rather than an interpolating function in the finite element method to calculate internal elastic forces. The proposed methodology not only models the deformation dynamics in continuum mechanics, but it also simplifies the complex deformation problem by simple setting the cellular neural network templates. |
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