update diff

Author: Your Named

diff.tex

@@ -1,7 +1,7 @@
 %% This is file `cag-template.tex',
 %DIF LATEXDIFF DIFFERENCE FILE
-%DIF DEL /dir/cag-template_old.tex   Fri Dec  2 01:47:24 2022
-%DIF ADD /dir/cag-template.tex       Fri Dec  2 01:47:24 2022
+%DIF DEL /dir/cag-template_old.tex   Mon Dec  5 16:00:12 2022
+%DIF ADD /dir/cag-template.tex       Mon Dec  5 16:00:12 2022
 %% 
 %% Copyright 2018 Elsevier Ltd
 %% 
@@ -159,7 +159,7 @@
 %% main text
 \section{Introduction}
 \label{sec1}
-\DIFaddbegin 
+\DIFdelbegin \DIFdel{The physics-based }\DIFdelend \DIFaddbegin 
 
 %DIF >  \begin{equation}
 %DIF >  \left[\begin{array}{ccc}
@@ -169,7 +169,7 @@ \section{Introduction}
 %DIF >  \end{array}\right]
 %DIF >  \end{equation}
 
-\DIFaddend The physics-based fluid simulation has great application value in \DIFdelbegin \DIFdel{the fields of both Computer-aided }\DIFdelend \DIFaddbegin \DIFadd{computer-aided }\DIFaddend Engineering (CAE) and Computer Graphics (CG) \DIFaddbegin \DIFadd{fields}\DIFaddend .
+\DIFadd{The physics based }\DIFaddend fluid simulation has great application value in \DIFdelbegin \DIFdel{the fields of both Computer-aided }\DIFdelend \DIFaddbegin \DIFadd{computer-aided }\DIFaddend Engineering (CAE) and Computer Graphics (CG) \DIFaddbegin \DIFadd{fields}\DIFaddend .
 Among all the simulation methods, the \emph{particle-based} approaches like \emph{Smoothed Particle Hydrodynamics} (SPH) have received much attention for their algorithmic efficiency and application flexibility~\cite{Ihmsen14}. 
 However, for the visualization of particle-based simulation results, tracing surfaces for particle-represented fluid has been the computation bottleneck of the whole process. Hence, how to efficiently visualize the simulated fluid while maintaining proper fidelity has become a hot research topic.
 
@@ -238,10 +238,10 @@ \subsection{Depth Information}
     % \setlength{\belowcaptionskip}{-5mm}
     \centering
     \subfigure[isotropic] {
-    \includegraphics[width=0.46\linewidth]{figs/isotropic.png}
+    \includegraphics[width=0.47\linewidth]{figs/isotropic.png}
     }    
     \subfigure[anisotropic] {
-    \includegraphics[width=0.46\linewidth]{figs/anisotropic.png}
+    \includegraphics[width=0.47\linewidth]{figs/anisotropic.png}
     } 
     \caption{Comparison of isotropic and anisotropic fluid particles.}
     \label{fig:figure3}
@@ -313,11 +313,11 @@ \subsection{Normal Reconstruction and Surface Shading}
     %DIF >  \setlength{\belowcaptionskip}{-5mm}
     \centering
     \subfigure[isotropic] {
-    \includegraphics[width=0.47\linewidth]{figs/figure5_1_new.png}
+    \includegraphics[width=0.48\linewidth]{figs/figure5_1_new.png}
     }
     \DIFaddFL{\hspace{-7pt}
     }\subfigure[anisotropic] {
-    \includegraphics[width=0.47\linewidth]{figs/figure5_2_new.png}
+    \includegraphics[width=0.48\linewidth]{figs/figure5_2_new.png}
     } 
     \caption{\DIFaddFL{Experimental comparison of isotropy and anisotropy in the dam break scenario.}}
     \label{fig:figure4}
@@ -494,32 +494,18 @@ \section{\DIFadd{Results and Analysis}}
 
 \DIFaddend The experiments below are performed using a hardware platform of AMD Ryzen 7 5800H @3.20 GHz, 32GB memory, and NVIDIA RTX 3060. The 3D graphics API OpenGL is used for particle rendering, and C++ is used as the hardware graphics interactive language to process logical operations. In addition, GLSL colouring language is used to calculate the fluid optical effect in GPU. The real-time performance of fluid is maintained during all experiments.
 
-% \DIFaddbegin \begin{figure}[!b]
-%     \centering
-%     \begin{overpic}
-%         [\DIFaddFL{width=}\linewidth]{\DIFaddFL{figs/figure9.png}}
-%         \put(6,-2)      {\footnotesize \DIFaddFL{Gaussian}}
-%         \put(25,-2)      {\footnotesize \DIFaddFL{Bilateral Gaussian}}
-%         \put(53,-2)      {\footnotesize \DIFaddFL{Curvature Flow}}
-%         \put(78,-2)      {\footnotesize \DIFaddFL{Narrow-Range}}
-%     \end{overpic}
-%     \caption{\DIFaddFL{From left to right are Gaussian filter, bilateral Gaussian filter, curvature flow filter and narrow-range filter. 
-%     %DIF >  All methods use the same number of iterations ($iter = 2$) except the curvature flow-based method with a larger number ($iter = 80$).
-%     }}
-%     \label{fig:figure6}
-% \end{figure}
-\begin{figure}[!b]
+\DIFaddbegin \begin{figure}[!b]
     \centering
     \begin{overpic}
-        [width=\linewidth]{figs/figure9.png}
-        \put(6,-2)      {\footnotesize Gaussian}
-        \put(25,-2)      {\footnotesize Bilateral Gaussian}
-        \put(53,-2)      {\footnotesize Curvature Flow}
-        \put(78,-2)      {\footnotesize Narrow-Range}
+        [\DIFaddFL{width=}\linewidth]{\DIFaddFL{figs/figure9.png}}
+        \put(6,-2)      {\footnotesize \DIFaddFL{Gaussian}}
+        \put(25,-2)      {\footnotesize \DIFaddFL{Bilateral Gaussian}}
+        \put(53,-2)      {\footnotesize \DIFaddFL{Curvature Flow}}
+        \put(78,-2)      {\footnotesize \DIFaddFL{Narrow-Range}}
     \end{overpic}
-    \caption{From left to right are Gaussian filter, bilateral Gaussian filter, curvature flow filter and narrow-range filter. 
-    % All methods use the same number of iterations ($iter = 2$) except the curvature flow-based method with a larger number ($iter = 80$).
-    }
+    \caption{\DIFaddFL{From left to right are Gaussian filter, bilateral Gaussian filter, curvature flow filter and narrow-range filter. 
+    %DIF >  All methods use the same number of iterations ($iter = 2$) except the curvature flow-based method with a larger number ($iter = 80$).
+    }}
     \label{fig:figure6}
 \end{figure}
 
@@ -528,39 +514,27 @@ \section{\DIFadd{Results and Analysis}}
 
 In addition, experimental verification is conducted for a fluid-solid coupling scenario, as shown in Fig.~\ref{fig:figure5}. In the fluid-solid coupling scenario, real-time fluid rendering based on the anisotropic algorithm shows better surface results with smoother surfaces, especially at the interface between the rigid body and liquid.
 
-% \DIFdelbegin %DIFDELCMD < \begin{figure}[!t]
-% %DIFDELCMD <     %%%
-% \DIFdelendFL \DIFaddbeginFL \begin{figure}[htpb]
-%     \DIFaddendFL \centering
-%     \begin{overpic}
-%         [width=\linewidth]{figs/\DIFdelbeginFL \DIFdelFL{figure9}\DIFdelendFL \DIFaddbeginFL \DIFaddFL{figure10}\DIFaddendFL .png}
-%         \DIFdelbeginFL %DIFDELCMD < \put(6,-2)      %%%
-% \DIFdelendFL \DIFaddbeginFL \put(6,-3)      \DIFaddendFL {\footnotesize Gaussian}
-%         \DIFdelbeginFL %DIFDELCMD < \put(25,-2)      %%%
-% \DIFdelendFL \DIFaddbeginFL \put(25.5,-3)     \DIFaddendFL {\footnotesize Bilateral Gaussian}
-%         \DIFdelbeginFL %DIFDELCMD < \put(53,-2)      %%%
-% \DIFdelendFL \DIFaddbeginFL \put(54,-3)     \DIFaddendFL {\footnotesize Curvature Flow}
-%         \DIFdelbeginFL %DIFDELCMD < \put(78,-2)      %%%
-% \DIFdelendFL \DIFaddbeginFL \put(78,-3)     \DIFaddendFL {\footnotesize Narrow-Range}
-%     \end{overpic}
-%     \caption{From left to right are Gaussian filter, bilateral Gaussian filter, curvature flow filter and narrow-range filter.%DIF <  All methods use the same number of iterations ($iter = 2$) except the curvature flow-based method with a larger number ($iter = 80$).
-%     }
-%     \DIFdelbeginFL %DIFDELCMD < \label{fig:figure6}
-% %DIFDELCMD < %%%
-% \DIFdelendFL \DIFaddbeginFL \label{fig:figure7}
-% \DIFaddendFL \end{figure}
-\begin{figure}[htpb]
-    \centering
+\DIFdelbegin %DIFDELCMD < \begin{figure}[!t]
+%DIFDELCMD <     %%%
+\DIFdelendFL \DIFaddbeginFL \begin{figure}[htpb]
+    \DIFaddendFL \centering
     \begin{overpic}
-        [width=\linewidth]{figs/figure10.png}
-        \put(6,-3)      {\footnotesize Gaussian}
-        \put(25.5,-3)     {\footnotesize Bilateral Gaussian}
-        \put(54,-3)     {\footnotesize Curvature Flow}
-        \put(78,-3)     {\footnotesize Narrow-Range}
+        [width=\linewidth]{figs/\DIFdelbeginFL \DIFdelFL{figure9}\DIFdelendFL \DIFaddbeginFL \DIFaddFL{figure10}\DIFaddendFL .png}
+        \DIFdelbeginFL %DIFDELCMD < \put(6,-2)      %%%
+\DIFdelendFL \DIFaddbeginFL \put(6,-3)      \DIFaddendFL {\footnotesize Gaussian}
+        \DIFdelbeginFL %DIFDELCMD < \put(25,-2)      %%%
+\DIFdelendFL \DIFaddbeginFL \put(25.5,-3)     \DIFaddendFL {\footnotesize Bilateral Gaussian}
+        \DIFdelbeginFL %DIFDELCMD < \put(53,-2)      %%%
+\DIFdelendFL \DIFaddbeginFL \put(54,-3)     \DIFaddendFL {\footnotesize Curvature Flow}
+        \DIFdelbeginFL %DIFDELCMD < \put(78,-2)      %%%
+\DIFdelendFL \DIFaddbeginFL \put(78,-3)     \DIFaddendFL {\footnotesize Narrow-Range}
     \end{overpic}
-    \caption{From left to right are Gaussian filter, bilateral Gaussian filter, curvature flow filter and narrow-range filter.}
-    \label{fig:figure7}
-\end{figure}
+    \caption{From left to right are Gaussian filter, bilateral Gaussian filter, curvature flow filter and narrow-range filter.%DIF <  All methods use the same number of iterations ($iter = 2$) except the curvature flow-based method with a larger number ($iter = 80$).
+    }
+    \DIFdelbeginFL %DIFDELCMD < \label{fig:figure6}
+%DIFDELCMD < %%%
+\DIFdelendFL \DIFaddbeginFL \label{fig:figure7}
+\DIFaddendFL \end{figure}
 
 \subsection{Combination with Popular Smoothing Filters}
 In this subsection, the anisotropic algorithm is combined with various popular smoothing filters to verify the effectiveness and practicability of the proposed scheme under actual application scenarios. The Gaussian filter, the bilateral Gaussian filter and the narrow-range filter use the same number of iterations ($iter=2$). The curvature flow filter uses more iterations ($iter=80$) to obtain flat surface results \DIFdelbegin \DIFdel{, }\DIFdelend at the cost of performance loss.