diff --git a/trunk/RTCSA_SS/03Design.tex b/trunk/RTCSA_SS/03Design.tex
index 5ac27cb..15d1660 100644
--- a/trunk/RTCSA_SS/03Design.tex
+++ b/trunk/RTCSA_SS/03Design.tex
@@ -31,20 +31,36 @@ bed, width of sensor square and the FOV of Grideye sensor.
 \subsection{Pose determination}
 
 We train a SRCNN model by the fused Grideye data and downscaled Lepton 3 image,
-and use it to upscle all following frames to SR frames. We lebeled some SR frames
+and use it to upscale all following frames to SR frames. We labeled some SR frames
 to two categories. One is lay on back and the other is lay on side. Since the input
 data is very small, we use a neural network consist one 2D convolution layer, one
 2D max pooling, one flatten and one densely-connected layer. The possibility of
 output has a very large various just after turning over because the model cannot
-distinguish the residual heat on bed and the person as Figure???? showen. This
+distinguish the residual heat on bed and the person as Figure~\ref{fig:pose}(a) shown. This
 situation will slowly disappear after one or two minutes.
 
 To determination the pose, first we use a median filter with a window size of five
-to filter out the noise. Than, find the curvex hull line of the upperbound and
-lowerbound of the data. Finally calculate the middle line of upperbound and lowerbound.
-Figure??? and ??? shows the data and these lines.
+to filter out the noise. Than, find the curve hull line of the upper bound and
+lower bound of the data. Finally calculate the middle line of upper bound and lower bound.
+Figure~\ref{fig:pose}(b) and (c) shows the data and these lines.
 
-We divide every 10 seconds data into a time window. If the middle line of the time window
+We divide every data into 10 second time windows. If the middle line of the time window
 is at the top one fifth, it is a lay on back. If it is at the bottom one fifth,
 it is a lay on side. If the trend of line is going up, it is lay on back. Otherwise, it
-is lay on side.
+is lay on side. To guarantee the confidence of result, we will only trust the pose if
+there are three continuously same output.
+
+\begin{figure}[ht]
+  \centering
+  \subfloat[Residual heat on bed]{
+    \includegraphics[width=0.3\columnwidth]{figures/Lepton_residual_heat.bmp}
+  }
+  \subfloat[Enhanced Images after Background Calibration]{
+    \includegraphics[width=0.3\columnwidth]{figures/MinMax.pdf}
+  }
+  \subfloat[Enhanced Images after Background Calibration]{
+    \includegraphics[width=0.3\columnwidth]{figures/Mid.pdf}
+  }
+  \caption{Background subtraction.}
+  \label{fig:pose}
+\end{figure}
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