  Automatic estimation of skinning transformations is a popular way to deform a
single reference shape into a new pose by providing a small number of control
parameters. We generalize this approach by efficiently enabling the use of
multiple exemplar shapes. Using a small set of representative natural poses, we
propose to express an unseen appearance by a low-dimensional linear subspace,
specified by a redundant dictionary of weighted vertex positions. Minimizing a
nonlinear functional that regulates the example manifold, the suggested
approach supports local-rigid deformations of articulated objects, as well as
nearly isometric embeddings of smooth shapes. A real-time non-rigid deformation
system is demonstrated, and a shape completion and partial registration
framework is introduced. These applications can recover a target pose and
implicit inverse kinematics from a small number of examples and just a few
vertex positions. The result reconstruction is more accurate compared to
state-of-the-art reduced deformable models.
