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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
+ 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 and validates the viability of
- skeleton-base identification.
+ the art facial recognition validates the viability of
+ skeleton-based identification.
\end{abstract}