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../../dokumentation/evolution1d/
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../../dokumentation/evolution3d/
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arbeit/ma.md
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arbeit/ma.md
@ -106,7 +106,7 @@ increases the efficiency of an evolutionary optimization\cite{Menzel2006}, which
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we will use later on.
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we will use later on.
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But this approach also has downsides as can be seen in
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But this approach also has downsides as can be seen in
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\cite[figure~7]{hsu1991dmffd}\todo{figure hier einfügen?}, as the tessellation
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\cite[figure~7]{hsu1991dmffd}\unsure{figure hier einfügen?}, as the tessellation
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of the invisible grid has a major impact on the deformation itself.
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of the invisible grid has a major impact on the deformation itself.
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All in all \ac{FFD} and \ac{DM-FFD} are still good ways to deform a high-polygon
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All in all \ac{FFD} and \ac{DM-FFD} are still good ways to deform a high-polygon
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@ -116,8 +116,9 @@ mesh albeit the downsides.
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## Wieso ist evo-Opt so cool?
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## Advantages of evolutional algorithms
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\improvement[inline]{Needs citations}
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The main advantage of evolutional algorithms is the ability to find optima of
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The main advantage of evolutional algorithms is the ability to find optima of
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general functions just with the help of a given error-function (or
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general functions just with the help of a given error-function (or
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fitness-function in this domain). This avoids the general pitfalls of
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fitness-function in this domain). This avoids the general pitfalls of
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@ -237,10 +238,6 @@ $\|\vec{G}\|_F = 1$, whereby $\|\cdot\|_F$ denotes the Frobenius-Norm.
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# Evaluation of Scenarios
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# Evaluation of Scenarios
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## Results of 1D Function Approximation
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## Spearman/Pearson-Metriken
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## Spearman/Pearson-Metriken
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- Was ist das?
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- Was ist das?
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@ -249,6 +246,36 @@ $\|\vec{G}\|_F = 1$, whereby $\|\cdot\|_F$ denotes the Frobenius-Norm.
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- Haben wir das gezeigt?
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- Haben wir das gezeigt?
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- Statistik, Bilder, blah!
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- Statistik, Bilder, blah!
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## Results of 1D Function Approximation
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\begin{figure}[!ht]
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\includegraphics[width=\textwidth]{img/evolution1d/20170830-evolution1D_5x5_100Times-all_appended.png}
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\caption{Results 1D}
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\end{figure}
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<!-- ![Improvement potential vs steps](img/evolution1d/20170830-evolution1D_5x5_100Times-all_improvement-vs-steps.png) -->
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<!-- -->
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<!-- ![Improvement potential vs evolutional error](img/evolution1d/20170830-evolution1D_5x5_100Times-all_improvement-vs-evo-error.png) -->
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<!-- -->
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<!-- ![Regularity vs steps](img/evolution1d/20170830-evolution1D_5x5_100Times-all_regularity-vs-steps.png) -->
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## Results of 3D Function Approximation
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\begin{figure}[!ht]
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\includegraphics[width=\textwidth]{img/evolution3d/20170926_3dFit_both_append.png}
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\caption{Results 3D}
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\end{figure}
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<!-- ![Improvement potential vs steps](img/evolution3d/20170926_3dFit_both_improvement-vs-steps.png) -->
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<!-- -->
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<!-- ![Improvement potential vs evolutional -->
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<!-- error](img/evolution3d/20170926_3dFit_both_improvement-vs-evo-error.png) -->
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<!-- -->
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<!-- ![Regularity vs steps](img/evolution3d/20170926_3dFit_both_regularity-vs-steps.png) -->
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# Schluss
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# Schluss
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HAHA .. als ob -.-
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HAHA .. als ob -.-
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BIN
arbeit/ma.pdf
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arbeit/ma.pdf
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@ -10,6 +10,7 @@ titlepage,
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% openany, % Kapitel koennen auch auf geraden Seiten starten
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% openany, % Kapitel koennen auch auf geraden Seiten starten
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% draft % schneller compillieren, Bild-dummy
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% draft % schneller compillieren, Bild-dummy
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% appendixprefix % Anhang mit Bezeichner
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% appendixprefix % Anhang mit Bezeichner
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xcolor=dvipsnames,
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]{scrbook}
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]{scrbook}
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%%%%%%%%%%%%%%% Literaturverzeichnisstil %%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%% Literaturverzeichnisstil %%%%%%%%%%%%%%%
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@ -232,7 +233,7 @@ control-points. Moreover this increases the efficiency of an
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evolutionary optimization\cite{Menzel2006}, which we will use later on.
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evolutionary optimization\cite{Menzel2006}, which we will use later on.
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But this approach also has downsides as can be seen in
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But this approach also has downsides as can be seen in
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\cite[figure~7]{hsu1991dmffd}\todo{figure hier einfügen?}, as the
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\cite[figure~7]{hsu1991dmffd}\unsure{figure hier einfügen?}, as the
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tessellation of the invisible grid has a major impact on the deformation
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tessellation of the invisible grid has a major impact on the deformation
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itself.
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itself.
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@ -242,13 +243,15 @@ high-polygon mesh albeit the downsides.
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\section{What is evolutional
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\section{What is evolutional
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optimization?}\label{what-is-evolutional-optimization}
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optimization?}\label{what-is-evolutional-optimization}
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\section{Wieso ist evo-Opt so cool?}\label{wieso-ist-evo-opt-so-cool}
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\section{Advantages of evolutional
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algorithms}\label{advantages-of-evolutional-algorithms}
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The main advantage of evolutional algorithms is the ability to find
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\improvement[inline]{Needs citations} The main advantage of evolutional
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optima of general functions just with the help of a given error-function
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algorithms is the ability to find optima of general functions just with
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(or fitness-function in this domain). This avoids the general pitfalls
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the help of a given error-function (or fitness-function in this domain).
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of gradient-based procedures, which often target the same error-function
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This avoids the general pitfalls of gradient-based procedures, which
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as an evolutional algorithm, but can get stuck in local optima.
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often target the same error-function as an evolutional algorithm, but
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can get stuck in local optima.
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This is mostly due to the fact that a gradient-based procedure has only
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This is mostly due to the fact that a gradient-based procedure has only
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one point of observation from where it evaluates the next steps, whereas
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one point of observation from where it evaluates the next steps, whereas
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@ -324,7 +327,8 @@ P(\vec{U}) := 1 - \|(\vec{1} - \vec{UU}^+)\vec(G)\|^2_F
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normalized to \(\|\vec{G}\|_F = 1\), whereby \(\|\cdot\|_F\) denotes the
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normalized to \(\|\vec{G}\|_F = 1\), whereby \(\|\cdot\|_F\) denotes the
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Frobenius-Norm.
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Frobenius-Norm.
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\chapter{Hauptteil}\label{hauptteil}
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\chapter{\texorpdfstring{Implementation of
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\acf{FFD}}{Implementation of }}\label{implementation-of}
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\section{Was ist FFD?}\label{was-ist-ffd}
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\section{Was ist FFD?}\label{was-ist-ffd}
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@ -340,11 +344,10 @@ Frobenius-Norm.
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Was folgt daraus?
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Was folgt daraus?
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\end{itemize}
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\end{itemize}
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\section{Szenarien vorstellen}\label{szenarien-vorstellen}
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\section{Test Scenario: 1D Function
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Approximation}\label{test-scenario-1d-function-approximation}
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\subsection{1D}\label{d}
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\subsection{Optimierungszenario}\label{optimierungszenario}
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\subsubsection{Optimierungszenario}\label{optimierungszenario}
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\begin{itemize}
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\begin{itemize}
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\tightlist
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\tightlist
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@ -352,7 +355,7 @@ Frobenius-Norm.
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Ebene -\textgreater{} Template-Fit
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Ebene -\textgreater{} Template-Fit
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\end{itemize}
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\end{itemize}
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\subsubsection{Matching in 1D}\label{matching-in-1d}
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\subsection{Matching in 1D}\label{matching-in-1d}
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\begin{itemize}
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\begin{itemize}
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\tightlist
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\tightlist
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@ -360,7 +363,7 @@ Frobenius-Norm.
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Trivial
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Trivial
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\end{itemize}
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\end{itemize}
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\subsubsection{Besonderheiten der
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\subsection{Besonderheiten der
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Auswertung}\label{besonderheiten-der-auswertung}
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Auswertung}\label{besonderheiten-der-auswertung}
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\begin{itemize}
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\begin{itemize}
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@ -379,9 +382,10 @@ Auswertung}\label{besonderheiten-der-auswertung}
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\end{itemize}
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\end{itemize}
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\end{itemize}
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\end{itemize}
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\subsection{3D}\label{d-1}
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\section{Test Scenario: 3D Function
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Approximation}\label{test-scenario-3d-function-approximation}
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\subsubsection{Optimierungsszenario}\label{optimierungsszenario}
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\subsection{Optimierungsszenario}\label{optimierungsszenario}
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\begin{itemize}
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\begin{itemize}
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\tightlist
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\tightlist
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@ -389,7 +393,7 @@ Auswertung}\label{besonderheiten-der-auswertung}
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Ball zu Mario
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Ball zu Mario
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\end{itemize}
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\end{itemize}
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\subsubsection{Matching in 3D}\label{matching-in-3d}
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\subsection{Matching in 3D}\label{matching-in-3d}
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\begin{itemize}
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\begin{itemize}
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\tightlist
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\tightlist
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@ -397,7 +401,7 @@ Auswertung}\label{besonderheiten-der-auswertung}
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alternierende Optimierung
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alternierende Optimierung
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\end{itemize}
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\end{itemize}
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\subsubsection{Besonderheiten der
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\subsection{Besonderheiten der
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Optimierung}\label{besonderheiten-der-optimierung}
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Optimierung}\label{besonderheiten-der-optimierung}
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\begin{itemize}
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\begin{itemize}
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@ -408,7 +412,7 @@ Optimierung}\label{besonderheiten-der-optimierung}
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Kriterien trotzdem gut
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Kriterien trotzdem gut
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\end{itemize}
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\end{itemize}
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\chapter{Evaluation}\label{evaluation}
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\chapter{Evaluation of Scenarios}\label{evaluation-of-scenarios}
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\section{Spearman/Pearson-Metriken}\label{spearmanpearson-metriken}
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\section{Spearman/Pearson-Metriken}\label{spearmanpearson-metriken}
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@ -426,6 +430,24 @@ Optimierung}\label{besonderheiten-der-optimierung}
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Statistik, Bilder, blah!
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Statistik, Bilder, blah!
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\end{itemize}
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\end{itemize}
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\section{Results of 1D Function
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Approximation}\label{results-of-1d-function-approximation}
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\begin{figure}[!ht]
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\includegraphics[width=\textwidth]{img/evolution1d/20170830-evolution1D_5x5_100Times-all_appended.png}
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\caption{Results 1D}
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\end{figure}
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\section{Results of 3D Function
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Approximation}\label{results-of-3d-function-approximation}
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\begin{figure}[!ht]
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\includegraphics[width=\textwidth]{img/evolution3d/20170926_3dFit_both_append.png}
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\caption{Results 3D}
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\end{figure}
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\chapter{Schluss}\label{schluss}
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\chapter{Schluss}\label{schluss}
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HAHA .. als ob -.-
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HAHA .. als ob -.-
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\includegraphics[width=1cm]{img/cd}
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\includegraphics[width=1cm]{img/cd}
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\end{center}\vspace{-15pt}\centering\footnotesize\texttt{#1}}}
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\end{center}\vspace{-15pt}\centering\footnotesize\texttt{#1}}}
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\renewcommand\vec[1]{\textbf{#1}}
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\renewcommand\vec[1]{\textbf{#1}}
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\newcommandx{\unsure}[2][1=]{\todo[linecolor=red,backgroundcolor=red!25,bordercolor=red,#1]{#2}}
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\newcommandx{\change}[2][1=]{\todo[linecolor=blue,backgroundcolor=blue!25,bordercolor=blue,#1]{#2}}
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\newcommandx{\info}[2][1=]{\todo[linecolor=OliveGreen,backgroundcolor=OliveGreen!25,bordercolor=OliveGreen,#1]{#2}}
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\newcommandx{\improvement}[2][1=]{\todo[linecolor=violet,backgroundcolor=violet!25,bordercolor=violet,#1]{#2}}
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\newcommandx{\thiswillnotshow}[2][1=]{\todo[disable,#1]{#2}}
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% \usepackage{teubner}
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% \usepackage{teubner}
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\usepackage{textcomp}
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\usepackage{textcomp}
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\usepackage{times}
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\usepackage{times}
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\usepackage{todonotes}
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\usepackage[colorinlistoftodos,prependcaption]{todonotes}
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\usepackage[ugly]{units} % \unit[Wert]{Einheit}
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\usepackage[ugly]{units} % \unit[Wert]{Einheit}
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% \usepackage{varioref} % schlaue referenzen: \vref{key} \vpageref[text]{key} \vrefrange, \vpagerefrange
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% \usepackage{varioref} % schlaue referenzen: \vref{key} \vpageref[text]{key} \vrefrange, \vpagerefrange
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\usepackage{verbatim} % \begin{comment} \end{comment}
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\usepackage{verbatim} % \begin{comment} \end{comment}
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\usepackage{wrapfig}
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\usepackage{wrapfig}
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% \usepackage{wasysym}
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% \usepackage{wasysym}
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\usepackage{xcolor}
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\usepackage[pdftex,dvipsnames]{xcolor}
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\usepackage{xspace} % intelligent \makro_ whitespace
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\usepackage{xspace} % intelligent \makro_ whitespace
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\usepackage{xargs} % use more than one optional parameter in new commands
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% ###### Caption ######
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% ###### Caption ######
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\captionsetup{margin=0.5cm, indention=0.5cm, font=small, labelfont=bf, format=plain,singlelinecheck=true,skip=3pt}
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\captionsetup{margin=0.5cm, indention=0.5cm, font=small, labelfont=bf, format=plain,singlelinecheck=true,skip=3pt}
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% openany, % Kapitel koennen auch auf geraden Seiten starten
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% openany, % Kapitel koennen auch auf geraden Seiten starten
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% draft % schneller compillieren, Bild-dummy
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% draft % schneller compillieren, Bild-dummy
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% appendixprefix % Anhang mit Bezeichner
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% appendixprefix % Anhang mit Bezeichner
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xcolor=dvipsnames,
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]{scrbook}
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]{scrbook}
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%%%%%%%%%%%%%%% Literaturverzeichnisstil %%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%% Literaturverzeichnisstil %%%%%%%%%%%%%%%
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