Wild Motion Unleashed: Markerless 3D Kinematics and Force Estimation in
  Cheetahs
Zico da Silva Stacy Shield Penny E. Hudson Alan M. Wilson Fred Nicolls Amir Patel
The complex dynamics of animal manoeuvrability in the wild is extremely
challenging to study. The cheetah ($\textit{Acinonyx jubatus}$) is a perfect
example: despite great interest in its unmatched speed and manoeuvrability,
obtaining complete whole-body motion data from these animals remains an
unsolved problem. This is especially difficult in wild cheetahs, where it is
essential that the methods used are remote and do not constrain the animal's
motion. In this work, we use data obtained from cheetahs in the wild to present
a trajectory optimisation approach for estimating the 3D kinematics and joint
torques of subjects remotely. We call this approach kinetic full trajectory
estimation (K-FTE). We validate the method on a dataset comprising synchronised
video and force plate data. We are able to reconstruct the 3D kinematics with
an average reprojection error of 17.69 pixels (62.94 $\%$ PCK using the
nose-to-eye(s) length segment as a threshold), while the estimates produce an
average root-mean-square error of 171.3 N ($\approx$ 17.16 $\%$ of peak force
during stride) for the estimated ground reaction force when compared against
the force plate data. While the joint torques cannot be directly validated
against ground truth data, as no such data is available for cheetahs, the
estimated torques agree with previous studies of quadrupeds in controlled
settings. These results will enable deeper insight into the study of animal
locomotion in a more natural environment for both biologists and roboticists.