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kenohori committed Feb 4, 2022
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2 changes: 1 addition & 1 deletion 3dbook.tex
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Expand Up @@ -144,7 +144,7 @@
\author{Ken Arroyo Ohori \hspace{7mm} Hugo Ledoux \hspace{7mm} Ravi Peters}
\date{\texttt{v0.8}}

\publishers{\includegraphics[width=0.7\linewidth]{brep/figs/cube.pdf}}
\publishers{\centerline{\includegraphics[width=\linewidth]{front-back/campus.png}}}

%----------------------------------------------------------------------------------------

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58 changes: 29 additions & 29 deletions bim/bim.tex

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2 changes: 1 addition & 1 deletion front-back/pre.tex
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Expand Up @@ -15,7 +15,7 @@

\medskip

v0.8---Initial release (for 2021--2022 Q3 course)
v0.8 --- 2022-02-04 --- Initial release (for 2021--2022 Q3 course)

\medskip
\medskip
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5 changes: 2 additions & 3 deletions front-back/preface.tex
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Expand Up @@ -12,13 +12,12 @@ \chapter*{Preface}
Each chapter corresponds to a lesson of the course, and each lesson is accompanied by a short video introducing the key ideas and/or explaining some parts of the lessons.
This book, the videos and other materials are freely available online on the website of the course: \url{https://3d.bk.tudelft.nl/courses/geo1004/}

\paragraph*{Contents}
The book describes the main ways in which the built environment is modelled in three dimensions, covering material from low-level data structures for generic 3D data to high-level semantic data models for cities.

\paragraph*{Who is this book for?}
The book is written for students in Geomatics at the MSc level, but we believe it can be also used at the BSc level.

Prerequisites are: GIS and a programming course at the introductory level.

The main prerequisites are GIS and programming.

\paragraph*{Acknowledgements.}
We thank all the students of first couple years of the course (2019--2020 and 2020--2021), who have helped us by pointing out errors and typos.
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22 changes: 9 additions & 13 deletions mat/mat.tex
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Expand Up @@ -10,38 +10,34 @@ \chapter{The Medial Axis Transform}%

The Medial Axis Transform (MAT) is yet another way to represent a 3D model.
It can be considered a \emph{dual} representation to the b-rep, similar to how the Voronoi diagram is dual to the Delaunay triangulation.
Contrary to the b-rep, that represents a model by describing explicitly its boundary surface, the MAT describes a model by its \emph{skeleton} (compare Figures~\ref{fig:gbm:brep} and \ref{fig:gbm:maxis}).
\begin{marginfigure}
Contrary to the b-rep, that represents a model by describing explicitly its boundary surface, the MAT describes a model by its \emph{skeleton} (compare Figures~\ref{fig:gbm:brep} and~\ref{fig:gbm:maxis}).
\begin{figure}
\centering
\begin{subfigure}[b]{0.47\linewidth}
\begin{subfigure}[b]{0.3\linewidth}
\centering
\includegraphics[width=\textwidth]{figs/gingerbreadman_whole.pdf}
\caption{}
\label{fig:gbm:whole}
\end{subfigure}
% \qquad%
\begin{subfigure}[b]{0.47\linewidth}
\begin{subfigure}[b]{0.3\linewidth}
\centering
\includegraphics[width=\textwidth]{figs/gingerbreadman_brep.pdf}
\caption{}
\label{fig:gbm:brep}
\end{subfigure}
% \qquad%
\begin{subfigure}[b]{0.50\linewidth}
\begin{subfigure}[b]{0.3\linewidth}
\centering
\includegraphics[width=\textwidth]{figs/gingerbreadman_skeleton.pdf}
\caption{}
\label{fig:gbm:maxis}
\end{subfigure}

\begin{subfigure}[b]{0.47\linewidth}
\end{subfigure}\\
\begin{subfigure}[b]{0.3\linewidth}
\centering
\includegraphics[width=\textwidth]{figs/gingerbreadman_mat.pdf}
\caption{}
\label{fig:gbm:mballs}
\end{subfigure}
% \qquad
\begin{subfigure}[b]{0.47\linewidth}
\begin{subfigure}[b]{0.3\linewidth}
\centering
\includegraphics[width=\textwidth]{figs/gingerbreadman_grassfire.pdf}
\caption{}
Expand All @@ -50,7 +46,7 @@ \chapter{The Medial Axis Transform}%

\caption{Different ways to represent the shape of gingerbread man (a). b) b-rep; c) Interior MAT; d) b-rep + MAT with medial balls; e) b-rep + contours of equal distance to it + MAT}
\label{fig:gingerman}
\end{marginfigure}
\end{figure}
Both the MAT and the b-rep contain exactly the same information and it is possible to convert one to the other without loss of information.

Compared to other shape representations, this skeleton structure makes different properties of the model explicit.
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