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A latex template to efficently design pretty posters. Posters are composited of
blocks with headings, that can be positioned easily on the page, using absolute
or relative positioning.
Download at:
http://www.brian-amberg.de/uni/poster/
Licence GPL
(c) 2007-2011 Brian Amberg and Reinhold Kainhofer
Documentation
See baposter_guide.pdf and the example files.

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\documentclass[final,letterpaper]{article}
\usepackage{url}
\usepackage{graphicx}
\usepackage{hyperref}
\usepackage{pdfpages}
\usepackage{geometry}
\newcommand{\baposter}{\texttt{baposter}}
\title{The baposter latex poster style}
\author{Brian Amberg and Reinhold Kainhofer}
\begin{document}
\maketitle
\begin{abstract}
This is still only a very rough documentation, but it should be better than no
documentation. If anything is unclear, please post a request (preferably with a
patch) at the bugtracker.
\end{abstract}
\section{Introduction}
\baposter{} is a LaTeX template to efficently design pretty posters for
scientific conferences. Posters are composited of blocks with headings, which
can be positioned easily on the page, using absolute or relative positioning. A
number of predefined styles can be composed to generate new color schemes and
ornaments.
\section{Usage}
Refer to the included example posters for the overall structure. I will document the different keys here.
The main environment for the poster is the \texttt{poster} environment. It has the following structure
\begin{verbatim}
\begin{poster}{
key=value options
}
{
Eye Catcher, empty if option eyecatcher=no
}
{
Poster Title
}
{
Poster Authors
}
{
University Logo
}
Definition of the boxes
\end{poster}
\end{verbatim}
\begin{center}
\setlength{\fboxsep}{0pt}
\fbox{\includegraphics[width=0.9\textwidth]{docs-structure}}
\end{center}
It should be immediately inside the
\begin{verbatim}
\begin{document}
\end{document}
\end{verbatim}
environment, or there will be blank pages.
Additionally, you can pass some options for page size selection directly to the class file.
\begin{verbatim}
\documentclass[class options]{baposter}
\end{verbatim}
\subsection{Class Options}
The class options are
\begin{description}
\item [landscape/portrait] Page Layout
\item [a0paper, a1paper, a2paper, a3paper, a4paper, archE] Predefined paper sizes
\item [paperwidth=length,paperheight=length] Width/Height of the paper. Do not use together with a0paper or other predefined paper sizes.
\item [margin=length] Page margin
\item [fontscale=real number] Scaling of the poster. The poster is typeset with
standard font sizes on a `fontscale times papersize' paper, and then scaled up
by 1/fontscale to the chosen paper size. This ensures good looking font sizes.
So if you need to fit more onto a poster, increase the fontscale option to get
smaller fonts. But be sure not to choose too small fonts, or your paper will be
awful. I find posters with small print a nuisance, and tend to spend more time
with well presented and concise content.
\item [showframe] Show a frame around the page, mainly useful for debugging.
\end{description}
\subsection{Poster Environment Options}
The available options are:
\begin{description}
\item[grid=\{yes,no\}] Display a grid, which can be useful during the layout phase.
\item[columns=4] Number of columns (default 4 in landscape and 3 in portrait format) (maximum number is 6)
\item[colspacing=length] Distance between the columns of the poster
\item[headerheight=length] Height of the main poster header as a length (not of the headers of the text boxes). Default value is \verb+0.1\textheight+.
\item[background=poster background type] Type of poster background. Possible values are
\begin{enumerate}
\item \verb+plain+: Plain background in one color (\verb+bgColorOne+)
\item \verb+shade-lr+: Horizontal background gradient (from \verb+bgColorOne+ to \verb+bgColorTwo+)
\item \verb+shade-tb+: Vertical background gradient (from \verb+bgColorOne+ to \verb+bgColorTwo+)
\item \verb+user+: Use the command \verb|\background{...}| to define your own background.
\item \verb+none+: No background at all.
\end{enumerate}
\begin{center}
\setlength{\fboxsep}{0pt}
\fbox{\includegraphics[width=0.21\textwidth,page=1]{docs-background}}
\fbox{\includegraphics[width=0.21\textwidth,page=2]{docs-background}}
\fbox{\includegraphics[width=0.21\textwidth,page=3]{docs-background}}
\fbox{\includegraphics[width=0.21\textwidth,page=4]{docs-background}}
\end{center}
\item[bgColorOne=pgf color name] First background color. For a plain, this color will be used. For a shaded background, this is the first color for the gradient.
\item[bgColorTwo=pgf color name] Second background color. This color will only be used for shaded backgrounds as the end color of the gradient.
\item[eyecatcher=\{yes,no\}] Should an eye catcher be shown on the
left of the title page. The eyecatcher itself is defined in the second
argument of the poster environment.
\end{description}
\subsection{Posterbox Environment Options}
\begin{description}
\item[borderColor=pgf color name] Color used for the borders of the poster boxes
\item[headerColorOne=pgf color name] First color of box header. Two colors can be used to define gradients.
\item[headerColorTwo=pgf color name] Second color of box header. Two colors can be used to define gradients.
\item[textborder=border type] Which kind of border should the lower part of the text boxes have. Possible values are:
\begin{enumerate}
\item none
\item bars
\item coils
\item triangles
\item rectangle
\item rounded
\item faded
\end{enumerate}
\includegraphics[width=0.9\textwidth]{docs-boxshape}
\item[headerborder=header border type] At which sides of the text box headers should we draw a border. Possible values are:
\begin{enumerate}
\item none
\item closed
\item open
\end{enumerate}
\includegraphics[width=0.9\textwidth]{docs-headerborder}
\item[headershape=header border shape] The type of ornament of the text box headers. Possible values are
\begin{enumerate}
\item rectangle
\item small-rounded
\item roundedright
\item roundedleft
\item rounded
\end{enumerate}
\includegraphics[width=0.9\textwidth]{docs-headershape}
\item[headershade=type of header shading] Which shading should be applied to the text box headers. Possible values are
\begin{enumerate}
\item plain
\item shade-lr
\item shade-tb
\item shade-tb-inverse
\end{enumerate}
\item[boxshade] which kind of shading is applied to the text boxes. Possible values are
\begin{enumerate}
\item shade-lr
\item shade-tb
\item plain
\item none
\end{enumerate}
\item[headerfont=font definition] Commands inserted before a text box header is typeset.
\item[headerFontColor=pgf color name] Color that the header is typeset in.
\item[linewidth=length] Width of the lines used when drawing the poster.
\end{description}
\section{Author and Licence}
The original author is Brian Amberg, and the class and documentation has been
greatly improved by Reinhold Kainhofer. The class is distributed under the GPL.
The current version and documentation can be found at:
\begin{center}
\url{http://www.brian-amberg.de/uni/poster/}
\end{center}
\end{document}

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\documentclass[portrait,fontscale=0.7,margin=0.2cm,paperwidth=8.2truecm, paperheight=11.88truecm,debug]{baposter}
\begin{document}
\begin{poster}{
background=none,
headerheight=\textheight,
}{}{\texttt{none}}{}{d}
\end{poster}
\begin{poster}{
background=plain,
bgColorOne=green!40,
headerheight=\textheight,
}{}{\texttt{plain}}{\texttt{bgColorOne=green!40}}{d}
\end{poster}
\begin{poster}{
background=shadelr,
bgColorOne=green!40,
bgColorTwo=yellow,
headerheight=\textheight,
}{}{\texttt{shade-lr}}{\texttt{bgColorOne=green!40}\\
\texttt{bgColorTwo=yellow}}{d}
\end{poster}
\begin{poster}{
background=shadetb,
bgColorOne=green!40,
bgColorTwo=yellow,
headerheight=\textheight,
}{}{\texttt{shade-tb}}{\texttt{bgColorOne=green!40}\\
\texttt{bgColorTwo=yellow}}{d}
\end{poster}
\end{document}

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\documentclass[portrait,fontscale=1,margin=0.2cm,paperwidth=15truecm, paperheight=3.5cm,debug]{baposter}
\begin{document}
\begin{poster}{
headerheight=0pt,
columns=5,
background=none,
linewidth=1pt,
borderColor=red,
% textborder=rectangle,
headershade=plain,
headerColorOne=green!60,
headershape=smallrounded,
headerfont={},
% below=notset,
height=0.45,
boxshade=plain,
eyecatcher=false,
boxheaderheight=1.5em,
boxColorOne=lightgray,
}{}{b}{}{}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{posterbox}[column=0,textborder=rectangle]{}
rectangle
\end{posterbox}
\begin{posterbox}[column=1,textborder=rounded]{}
rounded
\end{posterbox}
\begin{posterbox}[column=2,textborder=roundedsmall]{}
roundedsmall
\end{posterbox}
\begin{posterbox}[column=3,textborder=roundedleft]{}
roundedleft
\end{posterbox}
\begin{posterbox}[column=4,textborder=roundedright]{}
roundedright
\end{posterbox}
\begin{posterbox}[column=0,row=0.55,textborder=none]{}
none
\end{posterbox}
\begin{posterbox}[column=1,row=0.55,textborder=bars]{}
bars
\end{posterbox}
\begin{posterbox}[column=2,row=0.55,textborder=faded]{}
faded
\end{posterbox}
\begin{posterbox}[column=3,row=0.55,textborder=triangles]{}
triangles
\end{posterbox}
\begin{posterbox}[column=4,row=0.55,linewidth=0.5pt,textborder=coils]{}
coils
\end{posterbox}
\end{poster}
\end{document}

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\documentclass[portrait,fontscale=1,margin=0.2cm,paperwidth=15truecm, paperheight=1.5cm,debug]{baposter}
\begin{document}
\begin{poster}{
headerheight=0pt,
columns=3,
background=none,
% linewidth=0.5pt,
borderColor=red,
textborder=rectangle,
headershade=plain,
headerColorOne=green!60,
headershape=smallrounded,
% boxheaderheight=1.5em,
headerfont={},
boxColorOne=lightgray,
}{}{b}{}{d}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{posterbox}[column=0,boxColorOne=lightgray,height=bottom,headerborder=none]{none}
\end{posterbox}
\begin{posterbox}[column=1,boxColorOne=lightgray,height=bottom,headerborder=open]{open}
\end{posterbox}
\begin{posterbox}[column=2,boxColorOne=lightgray,height=bottom,headerborder=closed]{closed}
\end{posterbox}
\end{poster}
\end{document}

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\documentclass[portrait,fontscale=1,margin=0.2cm,paperwidth=15truecm, paperheight=1.5cm,debug]{baposter}
\begin{document}
\begin{poster}{
headerheight=0pt,
columns=5,
background=none,
linewidth=1pt,
borderColor=green!60,
textborder=rectangle,
headershade=plain,
headerColorOne=green!60,
% headershape=smallrounded,
headerfont={},
height=bottom,
boxColorOne=lightgray,
}{}{b}{}{d}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{posterbox}[column=0,headerfont={},headershape=rectangle]{rectangle}
\end{posterbox}
\begin{posterbox}[column=1,headerfont={},headershape=rounded]{rounded}
\end{posterbox}
\begin{posterbox}[column=2,headerfont={},headershape=smallrounded]{smallrounded}
\end{posterbox}
\begin{posterbox}[column=3,headerfont={},headershape=roundedleft]{roundedleft}
\end{posterbox}
\begin{posterbox}[column=4,headerfont={},headershape=roundedright]{roundedright}
\end{posterbox}
\end{poster}
\end{document}

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\documentclass[portrait,fontscale=0.7,margin=0.7cm,paperwidth=15truecm, paperheight=9truecm,debug]{baposter}
\begin{document}
\begin{poster}{
background=plain,
bgColorOne=lightgray!30,
headerheight=0.4\textheight,
columns=2,
headershade=plain,
headerColorOne=green!40,
boxColorOne=lightgray!75,
headershape=smallrounded,
textborder=roundedsmall,
linewidth=0.5pt,
borderColor=green,
headerborder=open,
}{\fbox{\parbox{1cm}{Logo}}}{\fbox{Poster Title}}{\fbox{Poster authors or subtitle}}{\fbox{\parbox{1cm}{Logo}}}
\begin{posterbox}[column=0]{Box 1}
Text of Box 1
\end{posterbox}
\begin{posterbox}[column=0,below=auto,height=bottom]{Box 2}
Text of Box 2
\end{posterbox}
\begin{posterbox}[column=1,height=bottom]{Box 2}
Text of Box 3
\end{posterbox}
\end{poster}
\end{document}

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ALL: poster.pdf
%.pdf: %.tex Makefile
pdflatex --enable-write18 $< && pdflatex $< && pdflatex $<
clean:
rm -f *.aux *.bbl *.blg *.log poster.pdf

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Revision info
=============
* $LastChangedDate: 2011-09-11 10:59:34 +0200 (V, 11 szept. 2011) $
* $LastChangedRevision: 129 $
* $LastChangedBy: rlegendi $
* $Id: README.md 129 2011-09-11 08:59:34Z rlegendi $
General Notes
=============
The poster was created with the help of Brian Amberg's [LaTeX Poster Template][].
The source is a bit commented, however, there are some minor caveats one should be aware of when compiling them.
Compiling the sources
=====================
I ran into some minor issues while using the template. Ain't sure ir it is an issue on other systems (I had Windows 7x64 with MiKTeX v2.8).
**The best way to evade them is to use pdflatex instead of latex to create the poster.** If it is required, `latex` may also be used, you can find some minor workarounds for the issues rising below.
No background image is displayed
--------------------------------
Clean the project by deleting the following files:
- `poster.aux`
- `poster.dvi`
- `poster.log`
Then recompile the sources. The background image should be displayed.
Backround image positioning problem workaround
--------------------------------------------------
1. First, change the document class options as follows:
%\documentclass[a0paper,portrait]{baposter}
\documentclass[a4paper,portrait]{baposter}
Just change `a0paper` to anything else (`a4paper` just worked for me, ain't sure about the others).
2. Compile the sources.
3. Change back the document class definition to `a0paper`, and the result should show the background image properly.
[LaTeX Poster Template]: http://www.brian-amberg.de/uni/poster/
"Brian's Template"

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% --------------------------------------------------------------------------- %
% Poster for the ECCS 2011 Conference about Elementary Dynamic Networks. %
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% $Id:: poster.tex 128 2011-09-11 08:57:12Z rlegendi $ %
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Properties of Elementary Random and Preferential Dynamic Networks
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%%% Authors %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
{
\vspace{1em} Richard O. Legendi, Laszlo Gulyas, George Kampis\\
{\smaller legendi@inf.elte.hu, lgulyas@colbud.hu, gkampis@colbud.hu}
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Sampling networks always involves the act of aggregation (e.g., when collecting longitudinal samples of networks). We sutdy how the cumulation window length effects the properties of the aggregated network.
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In our work the dynamic network is a series of graphs, that is, $DN = G_t(V_t,E_t)$, where $E_t \subseteq V_t \times V_t$ ($\forall t \geq 0$). The initial network, $G_0$, is considered as a parameter of the process. The \textbf{node set fixed} and we worked with an about \textbf{constant number of edges}. We assume that the evolution of the network can be described as the result of an edge creation and an edge deletion process. We define $G_t$ as the \textbf{snapshot network} and
{\smaller
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as the \textbf{cumulative network}.
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\textbf{ER1} $G_0$ is a random graph. Add each non-existing edge with $p_A$, delete each existing edge with $p_D$ probability. \\
\textbf{ER2} $G_0$ is a random graph. Add $k_A$ uniformly selected random new edges and delete $k_D$ existing edges. \\
\textbf{ER3} $G_0$ is a random graph. Rewire $k_{RW}$ edges. \\
\textbf{SPA} (\emph{Snapshot preferential}) $G_0$ is a scale free network. Add $k_A$ edges from a random node with preferential attachment based on the snapshot network. Delete $k_D$ existing edges. \\
\textbf{CPA} (\emph{Cumulative preferential}) $G_0$ is a scale free network. Add $k_A$ edges from a random node with preferential attachment based on the cumulative network. Delete $k_D$ existing edges.
}
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\bibitem{prevWork1} Laszlo Gulyas, Richard Legendi: \emph{Effects of Sample Duration on Network Statistics in Elementary Models of Dynamic Networks}, International Conference on Computational Science, Singapore (2011)
\bibitem{prevWork2} Laszlo Gulyas, Susan Khor, Richard Legendi and George Kampis \emph{Cumulative Properties of Elementary Dynamic Networks}, The International Sunbelt Social Network Conference XXXI (2011)
\bibitem{gulya-kampis1} Gulyas, Laszlo et al.: \emph{Betweenness Centrality Dynamics in Networks of Changing Density}. Presented at the 19th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2010)
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This research was partially supported by the Hungarian Government (KMOP-1.1.2-08/1-2008-0002 ) and the European Union's Seventh Framework Programme: DynaNets, FET-Open project no. FET-233847 (\url{http://www.dynanets.org}). The supports are gratefully acknowledged.
}
\headerbox{Dynamic Networks are Sensitive to Aggregation}{name=density,span=2,column=1,row=0}{
Network characteristics are extremely sensitive to minor changes in aggregation length. In our previous work \cite{prevWork1} \cite{prevWork2}, we studied the cumulative properties of Elementary Dynamic Network models over the complete time period (i.e., until they reach the stable point of a full network). Here we focus on the more realistc domain of sparse (cumulative) networks. We find that even when snapshot networks are stationary, \textbf{important network characteristics} (average path lenght, clustering, betwenness centrality) \textbf{are extremely sensitive to aggregation} (window length).
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\headerbox{Degree Distribution Radically Changes}
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Degree distributions are exceptionally sensitive to the length of the aggregation window. \textbf{The same dynamic network may produce a normal, lognormal or even power law distribution for different aggregation lenghts.} The digree distribution of the snapshot and cumulative network is inherently different. The following surfaces show the CPA model until it approaches the complete network.
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\vspace{-0.2em}
Taking slices of the cumulative 3D charts shows us how the degree distribution changes. The log-log charts below show the progression of these changes as the aggregation window gets larger.
\vspace{-0.2em}
\begin{center}
\includegraphics[angle=-90,width=0.49\linewidth]{ER1_cumulativeDegrees}
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\end{poster}
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\DeclareMathOperator*{\reshape}{reshape}
%\font\dsfnt=dsrom12
\newcommand{\SNN}{\ensuremath{\mathbb N}}
\newcommand{\SRR}{\ensuremath{\mathbb R}}
\newcommand{\SZZ}{\ensuremath{\mathbb Z}}
%-----------------------------------------------------------------------------
% Matrices of the shape model
\renewcommand{\a}{\VEC\alpha}
\renewcommand{\v}{\VEC v}
\renewcommand{\l}{\VEC l}
\newcommand*{\m}{\VEC{\mu}}
\newcommand*{\M}{\MAT{M}}
\renewcommand*{\P}{\MAT{\Pi}}
%\newcommand{\J}{\SET J}
\newcommand{\J}{\SET{P}}
\newcommand{\Active}{\mathcal{A}}
\newcommand{\Selection}{\mathbf{S}}
\newcommand{\AllSelections}{\mathfrak{S}}
\newcommand{\Params}{\VEC\Theta}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%% Some math symbols used in the text
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Multicol Settings
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\setlength{\columnsep}{1.5em}
\setlength{\columnseprule}{0mm}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Save space in lists. Use this after the opening of the list
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\newcommand{\compresslist}{%
\setlength{\itemsep}{1pt}%
\setlength{\parskip}{0pt}%
\setlength{\parsep}{0pt}%
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Begin of Document
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{document}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Here starts the poster
%%%---------------------------------------------------------------------------
%%% Format it to your taste with the options
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Define some colors
\definecolor{lightorange}{rgb}{0.9,0.4,0}
\definecolor{lightestorange}{rgb}{1,0.8,0.5}
\definecolor{darkorange}{rgb}{0.2,0.1,0}
\hyphenation{resolution occlusions}
%%
\begin{poster}%
% Poster Options
{
% Show grid to help with alignment
grid=false,
% Column spacing
colspacing=1em,
% Color style
bgColorOne=lightestorange,
bgColorTwo=white,
borderColor=darkorange,
headerColorOne=darkorange,
headerColorTwo=lightorange,
headerFontColor=white,
boxColorOne=lightestorange,
boxColorTwo=lightorange,
% Format of textbox
textborder=faded,
% Format of text header
eyecatcher=true,
headerborder=closed,
headerheight=0.1\textheight,
% textfont=\sc, An example of changing the text font
headershape=roundedright,
headershade=shadelr,
headerfont=\Large\bf\textsc, %Sans Serif
textfont={\setlength{\parindent}{1.5em}},
boxshade=plain,
% background=shade-tb,
background=plain,
linewidth=2pt
}
% Eye Catcher
{\includegraphics[height=7em]{images/search_tree_ex1-crop.pdf}}
% Title
{\bf\textsc{Optimal Landmark Detection using Shape Models and Branch and Bound}\vspace{0.5em}}
% Authors
{\textsc{\{ Brian.Amberg and Thomas.Vetter \}@unibas.ch}}
% University logo
{% The makebox allows the title to flow into the logo, this is a hack because of the L shaped logo.
\includegraphics[height=9.0em]{images/logo}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Now define the boxes that make up the poster
%%%---------------------------------------------------------------------------
%%% Each box has a name and can be placed absolutely or relatively.
%%% The only inconvenience is that you can only specify a relative position
%%% towards an already declared box. So if you have a box attached to the
%%% bottom, one to the top and a third one which should be in between, you
%%% have to specify the top and bottom boxes before you specify the middle
%%% box.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% A coloured circle useful as a bullet with an adjustably strong filling
\newcommand{\colouredcircle}{%
\tikz{\useasboundingbox (-0.2em,-0.32em) rectangle(0.2em,0.32em); \draw[draw=black,fill=lightblue,line width=0.03em] (0,0) circle(0.18em);}}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Problem}{name=problem,column=0,row=0}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Fitting statistical 2D and 3D shape models to images is necessary for a
variety of tasks, such as video editing and face recognition. Much progress
has been made on local fitting from an initial guess, but determining a close
enough initial guess is still an open problem. We propose a method to locate
fiducial points, which can then be used to initialize the fitting.
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Contributions}{name=contribution,column=0,below=problem}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
We overcome the inherent ambiguity in landmark detection by using global shape
information. We solve the combinatorial problem of selecting out of a large
number of candidate landmark detections the configuration which is best
supported by a shape model. Our method, as opposed to previous approaches,
always finds the globally optimal configuration.
The algorithm can be applied to a very general class of shape models and is
independent of the underlying feature point detector. Its theoretic optimality
is shown, and it is evaluated on a large face dataset.
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Results}{name=results,column=1,span=2,row=0}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
{
\smaller\centering
\begin{tabular}{@{}rccccccc@{}}
\begin{sideways}\makebox[0pt][c]{Success}\end{sideways} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_fa_success_1.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_fb_success_1.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_ql_success_1.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_qr_success_1.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_hl_success_1.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_hr_success_1.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_rc_success_1.pdf}} \\
&
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_fa_success_2.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_fb_success_2.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_ql_success_2.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_qr_success_2.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_hl_success_2.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_hr_success_2.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_rc_success_2.pdf}} \\
\midrule
\begin{sideways}\makebox[0pt][c]{Failure}\end{sideways} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_fa_fail.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_fb_fail.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_ql_fail.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_qr_fail.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_hl_fail.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_hr_fail.pdf}} &
\parbox[c]{0.11\linewidth}{\includegraphics[width=\linewidth]{images/l_rc_fail.pdf}}
\end{tabular}
}\\[-1em]
\begin{multicols}{2}
Some randomly chosen images from the color feret database for each
pose, and the detected landmark positions. The first two rows are success
cases, the last row shows a failure case.
\end{multicols}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Representation}{name=representation,column=2,below=results}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\centering\includegraphics[width=\linewidth]{images/representation.pdf}
Subsets of solutions are encoded as the Kartesian product of subsets of landmark candidates per fiducial point.
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Scaling Behaviour}{name=scaling,column=2,below=representation}{%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\smaller%
\centering{Runtime as a function of the number of false positives}\\[0em]%
\centering{{\includegraphics[width=0.9\linewidth]{images/typical_random_no_noise-crop.pdf}}}\\[0em]%
\centering{Runtime as a function of detection accuracy}\\[0em]%
\centering{{\includegraphics[width=0.9\linewidth]{images/typical_random_add_noise-crop.pdf}}}\\[0em]%
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{References}{name=references,column=0,above=bottom}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\smaller
\bibliographystyle{ieee}
\renewcommand{\section}[2]{\vskip 0.05em}
\begin{thebibliography}{1}\itemsep=-0.01em
\setlength{\baselineskip}{0.4em}
\bibitem{amberg11:bnb}
B.~Amberg, T. Vetter.
\newblock {O}ptimal {L}andmark {D}etection using {S}hape {M}odels and {B}ranch and {B}ound
\newblock In {\em ICCV '11}
\end{thebibliography}
\vspace{0.3em}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Source Code}{name=source,column=2,above=bottom}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\noindent
\begin{minipage}{\linewidth}
\begin{minipage}{0.75\linewidth}
\indent{}The source code is available at \\
\url{http://www.cs.unibas.ch/personen/amberg_brian/bnb/}
\end{minipage}\hfill%
\begin{minipage}{0.23\linewidth}
\hfill\includegraphics[width=\linewidth]{chart}
\end{minipage}
\end{minipage}
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Formulation}{name=formulation,column=0,below=contribution,above=references}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
The solution is constrained by a shape model
\begin{align}
M(\Params) &= (m_1(\Params), \dots, m_N(\Params))\\
m_i &: \SRR^{N_{\Params}}\to\SRR^2\nonumber
\end{align}
mapping model parameters~$\Params$ to image positions $m_i(\Params)$.
For each fiducial point $m_i$ a set of candidate positions
\begin{align}
L_i &= \{\l_i^1, \l_i^2, \dots\} & \l_i^j \in \SRR^2
\end{align}
is detected in the image.
The task is to assign to every model vertex one of the candidate positions
such that the shape model can be best fit to the selection $\Selection{}$, written as a tuple
\begin{align}
\Selection &=(j_1, j_2, \dots, j_N) & j_i &\in \SNN,\label{eqn:selection}
\end{align}
where $j_i$ is the index of a candidate of landmark $i$.
So we minimize the distance between the shape model and the image landmarks:
\begin{align}
\Selection^* &= \argmin_{\Selection=(j_1, \dots, j_N)} f(\Selection)\nonumber\\
f(\Selection) &= \min_{\Params} \sum_i \rho\left( \normLR{ m_i(\Params) - \l_i^{j_i} }\right)\quad.\label{eqn:cost}
\end{align}
Where $\rho: \SRR\to\SRR$ is a robust function, allowing us to handle missing
detections, and points which are invisible due to occlusion.
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Splitting Strategy}{name=strategy,column=1,above=bottom}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
{\smaller\centering{Runtime as a function of the splitting strategy}\\[-0.5em]
\includegraphics[width=0.95\linewidth]{images/typical_random_splitting_strategies.pdf}}
Different splitting strategies result in vastly different performance.
Note that `split into equal sized problems' is one of the worst strategies for
branch and bound.
}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\headerbox{Solution}{name=solution,column=1,row=0,below=results,above=strategy}{
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
This discrete optimization is solved by Branch and Bound, which is a method to minimize a function over a set. It requires us to (1) efficiently specify solution subsets, (2) determine a lower bound on the minimal cost of the solutions within a subset, and (3) specify a strategy to split a solution subset into two new subsets.
%\begin{enumerate}[itemsep=2pt,parsep=0pt]
% \item Start with the set of all elements $\SET Q=\{ \AllSelections \}$
% \item \textbf{Repeat}:
% \begin{enumerate}[itemsep=2pt,parsep=0pt,topsep=2pt]
% \item Take the minimal subset\vspace{-0.7em}
% \begin{align}
% \J_i &\leftarrow \argmin_{\J_i \in \SET Q} g(\J_i)\\
% \SET Q &\leftarrow \SET Q \setminus \{ \J_i \}\nonumber
% \end{align}
% \item
% \textbf{Return} $\Selection$ \textbf{if} $\J_i=\{\Selection\}$ is a single element.
% \item Split $\J_i$ into \vspace{-0.7em}
% \begin{align}
% \J_i^1 &\subset \J_i, \J_i^2 \subset \J_i\\\quad\text{ s.t. }\J_i &= \J_i^1 \cup \J_i^2.\nonumber
% \end{align}
% \item Add the new subsets to the candidates\vspace{-0.7em}
% \begin{align}
% \SET Q &\leftarrow \SET Q \cup \{ \J_i^1, \J_i^2 \}\nonumber
% \end{align}
% \end{enumerate}
%\end{enumerate}
The ingredients in our case are:
\begin{enumerate}
\item Solution subsets are created by taking subsets of landmark
candidates, and considering the Kartesian product of all selected landmark
candidates
\item We bound the cost for such a solution set by taking for each
landmark the minimal distance to the convex hull of the selected candidates
% \begin{align}
% g(\J) &= \min_{\Params} \sum_i \rho\left( d_{\text{convex hull}}(\l_i^{\J_i}, m_i(\Params)) \right)\\
% &< \min_{\Params} \min %\nonumber\\
% d_{\text{convex hull}}(\l_i^\J, \VEC x) &= \min_{c \in \text{convex hull}(\l_i^{\J})}\normLR{ x - c }.
% \end{align}
\item We found that splitting landmark candidates such that the convex hull of the resulting two landmark candidates are as distant as possible is most effective.
\end{enumerate}
}
\end{poster}
\end{document}

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