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@@ -93,7 +93,7 @@ pairs with a false positive rate of 6\%.
This experiment gives an idea of the noise variance level above which
it is not possible to consistently distinguish skeletons. This noise
level can be interpreted as follows in the person recognition
-setting. For this problem, a classifier can be built by first learning
+problem. For this problem, a classifier can be built be first learning
a \emph{skeleton profile} for each individual from all the
measurements in the training set. Then, given a new skeleton
measurement, the algorithm classifies it to the individual whose
@@ -105,9 +105,9 @@ there are two distinct sources of noise:
\item the noise of the new measurement: this comes from the device
doing the measurement.
\end{itemize}
-
-We will come back in section \label{sec:kinect} on the structure of
-the noise and its relation to the noise represented on the ROC curves.
+the combination of these two noises is what can be compared to the
+noise represented on the ROC curves. Section \label{sec:kinect} will
+give more insight on the structure of the noise.
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