Abstract

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 \begin{abstract}
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+  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}