MeshBased Inverse Kinematics
Robert W. Sumner Matthias Zwicker Craig Gotsman Jovan Popović
Top row: Ten lion example poses. Bottom row: A sequence of posing
operations. (A) Two handle vertices are chosen. (B) The front leg is
pulled forward and the lion continuously deforms as the constraint is
moved. (C) The red region is selected and frozen so that the front leg
can be edited in isolation. (D) A similar operation is performed to
adjust the tail. The final pose is different from any individual
example.

Abstract:
The ability to position a small subset of mesh vertices and produce a
meaningful overall deformation of the entire mesh is a
fundamental task in mesh editing and animation. However, the class of
meaningful deformations varies from mesh to mesh and depends on mesh
kinematics, which prescribes valid mesh configurations, and a
selection mechanism for choosing among them. Drawing an analogy to
the traditional use of skeletonbased inverse kinematics for posing
skeletons, we define meshbased inverse kinematics as the
problem of finding meaningful mesh deformations that meet specified
vertex constraints.
Our solution relies on example meshes to indicate the class of
meaningful deformations. Each example is represented with a feature
vector of deformation gradients that capture the affine
transformations which individual triangles undergo relative to a
reference pose. To pose a mesh, our algorithm efficiently searches
among all meshes with specified vertex positions to find the one that
is closest to some pose in a nonlinear span of the example feature
vectors. Since the search is not restricted to the span of example
shapes, this produces compelling deformations even when the
constraints require poses that are different from those observed in
the examples. Furthermore, because the span is formed by a nonlinear
blend of the example feature vectors, the blending component of our
system may also be used independently to pose meshes by specifying
blending weights or to compute multiway morph sequences.
SIGGRAPH 2005 Paper: [PDF 2.2M].
Video: [MP4 18M]
[WMV 20M]
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