A cellular neural network for deformable object modelling
This paper presents a new methodology for the deformation of soft objects bydrawing an analogy between cellular neural network (CNN) and elasticdeformation. An improved CNN model is developed to simulate thedeformation of soft objects. A fnite volume based method is presented to derivethe discrete d...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Book Chapter |
| Published: |
Springer
2006
|
| Online Access: | http://hdl.handle.net/20.500.11937/32335 |
| Summary: | This paper presents a new methodology for the deformation of soft objects bydrawing an analogy between cellular neural network (CNN) and elasticdeformation. An improved CNN model is developed to simulate thedeformation of soft objects. A fnite volume based method is presented to derivethe discrete dijferential operators over irregular nets for obtaining the internalelastic forces. The proposed methodology not only models the deformationdynamics in continuum mechanics, but it also simplifies the complexdeformation problem with simple setting CNN templates. |
|---|