Paper
17 November 2008 Shape metamorphosis using deformable spherical maps
Archana Sangole, George K. Knopf
Author Affiliations +
Proceedings Volume 7266, Optomechatronic Technologies 2008; 72661D (2008) https://doi.org/10.1117/12.817410
Event: International Symposium on Optomechatronic Technologies, 2008, San Diego, California, United States
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Archana Sangole and George K. Knopf "Shape metamorphosis using deformable spherical maps", Proc. SPIE 7266, Optomechatronic Technologies 2008, 72661D (17 November 2008); https://doi.org/10.1117/12.817410
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KEYWORDS
Spherical lenses

Strontium

Head

Detection and tracking algorithms

Optical spheres

Data modeling

Visualization

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