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\begin{abstract}
This paper explores a novel approach for person recognition based on
skeletal measurements. After showing that exact measurements allow
for exact 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 and validates the viability of
skeleton-base identification.
\end{abstract}
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