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Proceedings Paper

Shape metamorphosis using deformable spherical maps
Author(s): Archana Sangole; George K. Knopf
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Paper Abstract

The transformation of a surface mesh from one form to another requires information about object geometry and node topology. Establishing a valid correspondence between the mesh nodes of the two bounding objects is critical for smooth shape deformation. The complexity of the task is increased if the meshes are originally created from separate sets of measured surface data. The shape transformation technique described in this paper utilizes a self-organizing feature map (SOFM), with a fixed number of nodes and known spherical topology, to fit a tessellated surface mesh around the reference data set. The nodal mesh is then allowed to gradually deform and assume the underlying geometry of the target data set. The mesh deformation is achieved through an unsupervised learning algorithm that iteratively modifies the location of nodes based on randomly selected coordinate points from the target surface. Furthermore, regional shape changes occur because the algorithm adjusts the location of nearest neighboring nodes in the evolving mesh. The correspondence between the neighboring nodes in the two bounding shapes is maintained during the intermediate stages of shape interpolation process. The algorithm's performance is illustrated using scanned surface data from several freeform objects.

Paper Details

Date Published: 17 November 2008
PDF: 12 pages
Proc. SPIE 7266, Optomechatronic Technologies 2008, 72661D (17 November 2008); doi: 10.1117/12.817410
Show Author Affiliations
Archana Sangole, Ecole Polytechnique (Canada)
Univ. of Montreal (Canada)
George K. Knopf, The Univ. of Western Ontario (Canada)


Published in SPIE Proceedings Vol. 7266:
Optomechatronic Technologies 2008
John T. Wen; Dalibor Hodko; Yukitoshi Otani; Jonathan Kofman; Okyay Kaynak, Editor(s)

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