\begin{abstract}
  This paper explores a novel approach for person recognition based on
  skeletal measurements. After showing that exact measurements allow
  for accurate recognition, we study two algorithmic approaches for
  identification in case of approximate measurements. A real-life
  experiment with 25 people and measurements obtained from the Kinect
  range camera gives us promising results and comparison with state of
  the art facial recognition validates the viability of
  skeleton-based identification.
\end{abstract}

