  We present a real-time cloth animation method for dressing virtual humans of
various shapes and poses. Our approach formulates the clothing deformation as a
high-dimensional function of body shape parameters and pose parameters. In
order to accelerate the computation, our formulation factorizes the clothing
deformation into two independent components: the deformation introduced by body
pose variation (Clothing Pose Model) and the deformation from body shape
variation (Clothing Shape Model). Furthermore, we sample and cluster the poses
spanning the entire pose space and use those clusters to efficiently calculate
the anchoring points. We also introduce a sensitivity-based distance
measurement to both find nearby anchoring points and evaluate their
contributions to the final animation. Given a query shape and pose of the
virtual agent, we synthesize the resulting clothing deformation by blending the
Taylor expansion results of nearby anchoring points. Compared to previous
methods, our approach is general and able to add the shape dimension to any
clothing pose model. %and therefore it is more general. Furthermore, we can
animate clothing represented with tens of thousands of vertices at 50+ FPS on a
CPU. Moreover, our example database is more representative and can be generated
in parallel, and thereby saves the training time. We also conduct a user
evaluation and show that our method can improve a user's perception of dressed
virtual agents in an immersive virtual environment compared to a conventional
linear blend skinning method.
