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authorJon Whiteaker <jbw@berkeley.edu>2012-08-13 15:46:25 -0700
committerJon Whiteaker <jbw@berkeley.edu>2012-08-13 15:46:25 -0700
commitcef7389306738767b76ba32437150fd20880c350 (patch)
tree3b6086b3bdbd4e33480e731addd9f0e1f6afafb4 /experimental.tex
parentff1e46e5bfa8ba1aad2f8f11aa3b701ac76a3847 (diff)
downloadkinect-cef7389306738767b76ba32437150fd20880c350.tar.gz
made reducing the noise section more clear
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\subsection{Reducing the noise}
-For the final experiment, we study what happens when the noise is reduced on
-the Kinect.
+For the final experiment, we explore the potential of skeleton recognition with
+a higher resolution depth camera, as has been speculated for the Kinect
+2~\footnote{\url{http://www.eurogamer.net/articles/2011-11-25-kinect-2-so-accurate-it-can-lip-read}}.
+Since a higher resolution camera is not readily available, we simulate a higher
+resolution by artificially reducing the noise from our Kinect dataset.
%Predicting potential improvements of the prediction rate of our
%algorithm is straightforward. The algorithm relies on 9 features only.
%\xref{sec:uniqueness} shows that 6 of these features alone are sufficient to
%perfectly distinguish two different skeletons at a low noise level. Therefore,
%the only source of classification error in our algorithm is the dispersion of
%the observed limbs' lengths away from the exact measurements.
-To simulate a reduction of the noise level, the dataset is modified as
-follows: we compute the average profile of each person, and for each frame we
-divide the empirical variance from the average by 2. Formally, using
-the same notations as in Section~\ref{sec:mixture of Gaussians}, each
-observation $\bx_i$ is replaced by $\bx_i'$ defined by:
+To simulate a reduction of the noise level, the dataset is modified as follows:
+we measure the average skeletal profile of each person, and for each frame
+we divide the empirical variance from the average by 2. Formally, using the
+same notations as in Section~\ref{sec:mixture of Gaussians}, each observation
+$\bx_i$ is replaced by $\bx_i'$ defined by:
\begin{equation}
\bx_i' = \bar{\bx}_{y_i} + \frac{\bx_i-\bar{\bx}_{y_i}}{2}
\end{equation}