From c0d3d3e00c3990609fbb8f8a1444020080af8ebc Mon Sep 17 00:00:00 2001
From: Thibaut Horel <thibaut.horel@gmail.com>
Date: Thu, 1 Mar 2012 13:56:29 -0800
Subject: End of the data set table

---
 experimental.tex | 23 ++++++++++++-----------
 1 file changed, 12 insertions(+), 11 deletions(-)

(limited to 'experimental.tex')

diff --git a/experimental.tex b/experimental.tex
index dfd4916..c0a559b 100644
--- a/experimental.tex
+++ b/experimental.tex
@@ -35,8 +35,8 @@ The original dataset consists of the sequence of all the frames where
 a skeleton was detected by the Kinect SDK. For each frames the
 following data is available:
 \begin{itemize}
-\item the 3D coordinates of 20 body joints
-\item a color picture recorded by the video camera
+\item the 3D coordinates of 20 body joints,
+\item a color picture recorded by the video camera.
 \end{itemize}
 For some of frames, one or several joints are occluded by another part
 of the body. In those cases, the coordinates of these joints are
@@ -60,12 +60,12 @@ distance from the skeleton joints to the camera is increasing.
 Several reductions are then applied to the data set to extract
 \emph{features} from the raw data:
 \begin{itemize}
-\item from the joints coordinates, the lengths of 15 body parts are
+\item From the joints coordinates, the lengths of 15 body parts are
   computed. These are distances between two contiguous joints in the
   human body. If one of the two joints of a body part is not present
   or inferred in a frame, the corresponding body part is reported as
   absent for the frame.
-\item the number of features is then reduced to 9 by using the
+\item The number of features is then reduced to 9 by using the
   vertical symmetry of the human body: if two body parts are symmetric
   about the vertical axis, we bundle them into one feature by
   averaging their lengths. If only one of them is present, we take the
@@ -74,24 +74,25 @@ Several reductions are then applied to the data set to extract
   are: Head-ShoulderCenter, ShoulderCenter-Shoulder, Shoulder-Elbow,
   Elbow-Wrist, ShoulderCenter-Spine, Spine-HipCenter,
   HipCenter-HipSide, HipSide-Knee, Knee-Ankle.
-\item finally, all the frames where any of the 9 features is missing
+\item Finally, all the frames where any of the 9 features is missing
   are filtered out.
 \end{itemize}
 
-Table \ref{tab:dataset} summarizes some statistics about the resulting
-dataset.
-
 \begin{table}
 \begin{center}
-\begin{tabular}{l|r||l|l|l}
+\begin{tabular}{|l|r||r|r|r|}
+\hline
 Number of people & 25 & $k\leq 5$ & $5\leq k\leq 20$ & $k\geq 20$\\
 \hline
 Number of frames & 15945 & 1211 & 561 & 291 \\
 \hline
-Number of runs & 244 & \\
+Number of runs & 244 & 18 & 8 & 4\\
+\hline
 \end{tabular}
 \end{center}
-\caption{}
+\caption{Data set statistics. The right part of the table shows the
+average numbers for different intervals of $k$, the rank of a person
+in the ordering given by the number of frames.}
 \label{tab:dataset}
 \end{table}
 
-- 
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