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    A deformable model with cellular neural network

    Access Status
    Fulltext not available
    Authors
    Zhong, Yongmin
    Shirinzadeh, B.
    Alici, G.
    Smith, J.
    Date
    2005
    Type
    Conference Paper
    
    Metadata
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    Citation
    Zhong, Y. and Shirinzadeh, B. and Alici, G. and Smith, J. 2005. A deformable model with cellular neural network, in Proceedings of the International Conference on Computer Animation and Social Agents 2005 (CASA2005), Oct 17-19 2005, pp. 25-30. Hong Kong: The Hong Kong Polytechnic University.
    Source Title
    Proceedings of the International Conference on Computer Animation and Social Agents
    Source Conference
    International Conference on Computer Animation and Social Agents
    ISSN
    0097-8493
    URI
    http://hdl.handle.net/20.500.11937/5856
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a new methodology for deformable models by drawing an analogy between cellular neural network (CNN) and elastic deformation. The potential energy stored in an elastic body as a result of a deformation caused by an external force is propagated among mass points by the local connectivity of cells and the CNN dynamics. An improved CNN model is developed for propagating the energy generated by the external force on the object surface. A method is presented to derive the internal forces from the potential energy distribution established by the CNN. The methodology proposed in this paper can not only deal with large-range deformation, but it can also accommodate both isotropic and anisotropic materials by simply modifying capacitors of cells. Examples are presented to demonstrate the efficacy of the proposed methodology.

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