  We present a novel retargeting algorithm that transfers the musculature of a
reference anatomical model to new bodies with different sizes, body
proportions, muscle capability, and joint range of motion while preserving the
functionality of the original musculature as closely as possible. The geometric
configuration and physiological parameters of musculotendon units are estimated
and optimized to adapt to new bodies. The range of motion around joints is
estimated from a motion capture dataset and edited further for individual
models. The retargeted model is simulation-ready, so we can physically simulate
muscle-actuated motor skills with the model. Our system is capable of
generating a wide variety of anatomical bodies that can be simulated to walk,
run, jump and dance while maintaining balance under gravity. We will also
demonstrate the construction of individualized musculoskeletal models from
bi-planar X-ray images and medical examinations.
