git-svn-id: http://newslabx.csie.ntu.edu.tw/svn/Ginger@66 5747cdd2-2146-426f-b2b0-0570f90b98ed

trunk/RTCSA_SS/04Evaluation.tex

@@ -23,8 +23,9 @@ Lepton 3, and align them at the same timestamps. Figure~\ref{fig:resolution_comp
 	\label{fig:resolution_compare}
 \end{figure}
 
-For training the pose recognization model, we collect 200 images of lay on back and 400 images
+For training the pose recognition model, we collect 200 images of lay on back and 400 images
 of lay on right or left side. The result shows that the accuracy of single frame detection
 can be improved about 5\% by SRCNN.
 
-The accuracy of pose detection is about 67\% and turning over datection is 56\%.
+We let a person lay on bed and change his pose every minutes. The pose is repeating
+lay on back, lay on left, lay on back and lay on right.

trunk/RTCSA_SS/05Conclusion.tex

@@ -3,7 +3,7 @@
 In this paper, we use the SRCNN to improve the resolution of thermal sensor, and
 detect the pose of each frame.
 The result shows that Super-resolution can slightly improve the accuracy of pose
-detection. We develop a method to detect the turning over. It has about 67\% accuracy
-even when the accuracy of pose detection is only ???\%.
+detection. We develop a method to detect the turning over. It has about 
+50\% recall rate and 83\% precision.