  In inertial motion capture, a multitude of body segments are equipped with
inertial sensors, consisting of 3D accelerometers and 3D gyroscopes. Using an
optimization-based approach to solve the motion capture problem allows for
natural inclusion of biomechanical constraints and for modeling the connection
of the body segments at the joint locations. The computational complexity of
solving this problem grows both with the length of the data set and with the
number of sensors and body segments considered. In this work, we present a
scalable and distributed solution to this problem using tailored message
passing, capable of exploiting the structure that is inherent in the problem.
As a proof-of-concept we apply our algorithm to data from a lower body
configuration.
