Skip to content

Commit

Permalink
results + corrections
Browse files Browse the repository at this point in the history
  • Loading branch information
Ethiy committed Oct 19, 2018
1 parent f46bffc commit 97cc279
Showing 1 changed file with 57 additions and 26 deletions.
83 changes: 57 additions & 26 deletions presentation.tex
View file
Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,7 @@


\newacronym{acr::lod}{LoD}{Level of Detail}
\newacronym{acr::elod}{eLoD}{evalution Level of Detail}
\newacronym{acr::elod}{eLoD}{evaluation Level of Detail}
\newacronym{acr::lidar}{LiDAR}{Light Detection and Ranging}
\newacronym{acr::dsm}{DSM}{Digital Surface Model}
\newacronym{acr::gui}{GUI}{Graphical User Interface}
Expand Down Expand Up @@ -90,20 +90,20 @@
\only<1-4>{
\begin{itemize}[label=$\blacktriangleright$, font=\color{IGNGreen}, itemsep=2em]
\item<1-> Automatic urban modeling: an active research area~\citep{Musialski2012};
\item<2-> Results seamless but lack generality~\citep{rottensteiner2014results};
\item<2-> Results seamless but lack generality and often erroneous~\citep{rottensteiner2014results};
\begin{itemize}[label=$\longrightarrow$]
\item<3-> labourious manual corrections.
\end{itemize}
\item<4-> Urban 3D model semantic diagnostic not well studied~\citep{nguatem2017modeling};
\item<4-> Urban 3D model semantic diagnostic \textcolor{purple}{not well studied}~\citep{nguatem2017modeling};
\end{itemize}
}
\only<5->{
\begin{itemize}[label=Goal $\longrightarrow$, font=\color{purple}, leftmargin=2cm]
\item<5-> Detect and describe semantic errors that affects building 3D models.
\item<5-> Detect and describe semantic errors that affect building 3D models.
\end{itemize}
\begin{itemize}[label=$\blacktriangleright$, font=\color{IGNGreen}, itemsep=2em]
\item<6-> Semantic errors independent from \textbf{reconstruction methods} and \textbf{urban scenes}.
\item<7-> Transferablility, and hence scallability, of the evalution method.
\item<7-> \textbf{Transferability}, and hence scallability, of the evaluation method.
\end{itemize}
}
\end{frame}
Expand All @@ -120,15 +120,15 @@
\begin{frame}{Main ideas behind our approach}
\begin{itemize}[label=$\blacktriangleright$, font=\color{IGNGreen}, itemsep=2em]
\item<1-> Compile errors that affect building models in a taxonomy;
\item<2-> Evaluation at building level $\Longrightarrow$ formulated as a supervized classification problem;
\item<3-> Study in a \textbf{2.5D overhead} modeling setting.
\item<2-> Evaluation at building level $\Longrightarrow$ formulated as a supervised classification problem;
\item<3-> Study in a \textbf{2.5D overhead (aerial)} modeling setting.
\end{itemize}
\end{frame}
\begin{frame}{Taxonomy structure}
Two criteria determine the taxonomy structure:
\begin{itemize}[label=$\blacktriangleright$, font=\color{IGNGreen}, itemsep=2em]
\item<2-> the \acrshort{acr::lod};
\item<3-> the \emph{finesse}: the semantic evaluation level.
\item<2-> the \textbf{\acrfull{acr::lod}};
\item<3-> the \textbf{\emph{finesse}}: the semantic evaluation level.
\end{itemize}
~\\
\uncover<4->{
Expand Down Expand Up @@ -223,7 +223,7 @@
\end{figure}
\end{frame}

\begin{frame}{The evalutation pipeline sketch}
\begin{frame}{The evaluation pipeline sketch}
\begin{figure}
\includegraphics[width=\textwidth]{graphical_abstract}
\end{figure}
Expand Down Expand Up @@ -252,26 +252,51 @@
\end{frame}

\section{Experiments}
\begin{frame}{Used data}
\begin{frame}{Results using all features}
\begin{table}
\begin{center}
\scriptsize
\begin{tabular}{c c c c}
\toprule
& Elancourt & Nantes & Paris 13 \\
& Elancourt & Nantes & Paris 13 \\
\midrule
\# samples & 2009 & 748 & 478 \\
\bottomrule
\end{tabular}
\caption{\scriptsize Dataset statistics}
\uncover<2->{
\begin{tabular}{|x{1cm} | x{1.3cm} x{1.3cm} | x{1.2cm} x{1.2cm} | x{1.2cm} x{1.2cm}|}
\hline
& \multicolumn{2}{x{3cm}|}{\textbf{Elancourt (10-cross val.)}} & \multicolumn{2}{x{2.4cm}|}{\textbf{Elancourt $\rightarrow$ Nantes}} & \multicolumn{2}{x{2.5cm}|}{\textbf{Elancourt $\rightarrow$ Paris 13}}\\
\cline{2-7}
&\textbf{Recall} & \textbf{Prec.} & \textbf{Recall} & \textbf{Prec.} & \textbf{Recall} & \textbf{Prec.} \\
\hline
\textit{BOS} & 90.83 & 76.14 & \textcolor{IGNDarkGreen}{93.12} & \textcolor{red}{42.61} & \textcolor{IGNDarkGreen}{96.53} & \textcolor{red}{43.82} \\
\hline
\textit{BUS} & 39.32 & 71.81 & \textcolor{red}{8.82} & 66.67 & \textcolor{red}{0} & \textcolor{red}{---} \\
\hline
\textit{BImB} & 16.75 & 68.0 & \textcolor{red}{2.02} & 33.33 & \textcolor{red}{0} & \textcolor{red}{---} \\
\hline
\textit{BInT} & 11.11 & 91.67 & 0.88 & 100 & 3.95 & 50.0 \\
\hline
\hline
\textit{FOS} & 98.91 & 98.84 & \textcolor{IGNDarkGreen}{98.33} & \textcolor{IGNDarkGreen}{97.92} & \textcolor{IGNDarkGreen}{97.19} & \textcolor{IGNDarkGreen}{97.58} \\
\hline
\textit{FUS} & 1.27 & 66.67 & \textcolor{IGNDarkGreen}{13.81} & \textcolor{IGNDarkGreen}{63.04} & 8.36 & 95.83 \\
\hline
\textit{FImB} & 7.42 & 100 & \textcolor{IGNDarkGreen}{46.34} & 65.52 & 11.80 & 60.71 \\
\hline
\textit{FImT} & 3.33 & 100 & 9.09 & 100 & 0 & 0 \\
\hline
\textit{FIG} & 79.02 & 71.82 & \textcolor{IGNDarkGreen}{94.17} & 70.70 & \textcolor{IGNDarkGreen}{86.16} & \textcolor{IGNDarkGreen}{88.47} \\
\hline
\end{tabular}
\caption{\scriptsize Test results using \textbf{Random Forest} ($max\ depth = 4$ \& $\# trees = 1000$) trained on Elancourt.}
}
\end{center}
\end{table}
\end{frame}
\begin{frame}{Results}

\end{frame}
\begin{frame}{Discussion}

\end{frame}
\begin{frame}{Some failure cases}
\begin{frame}{Some failure cases on Elancourt}
\begin{figure}
\begin{center}
\tiny
Expand All @@ -282,23 +307,29 @@
\textbf{Errors} & \textbf{G.T.} & \textbf{Pred.} & \textbf{Errors} & \textbf{G.T.} & \textbf{Pred.} & \textbf{Errors} & \textbf{G.T.} & \textbf{Pred.} & \textbf{Errors} & \textbf{G.T.} & \textbf{Pred.}\\
\hline
\textit{BOS} & \xmark & \cmark & \textit{BUS} & \xmark & \cmark & \textit{BOS} & \cmark & \cmark & \textit{BOS} & \cmark & \xmark \\
Valid & \cmark & \xmark & \textit{FImS} & \cmark & \xmark & \textit{FUS} & \cmark & \xmark & \textit{FOS} & \cmark & \xmark \\
Valid & \cmark & \xmark & \textit{FIG} & \cmark & \xmark & \textit{FUS} & \cmark & \xmark & \textit{FOS} & \cmark & \xmark \\
& & & \textit{FOS} & \cmark & \xmark & & & & \textit{BUS} & \cmark & \xmark \\
& & & & & & & & & \textit{BInF} & \cmark & \cmark \\
& & & & & & & & & \textit{BImB} & \cmark & \cmark \\
\hline
\end{tabular}
\end{center}
\end{figure}
\end{frame}

\section{Conclusion}
\begin{frame}{Conclusion \& Perspectives}
\begin{itemize}[label=$\blacktriangleright$, font=\color{IGNGreen}, itemsep=2em]
\item \textbf{Flexible, robust and hierarchical} taxonomy agnostic to inputs;
\begin{frame}{\textcolor{yellow}{Conclusion} \& \textcolor{purple}{Perspectives}}
\begin{itemize}[label=$\blacktriangleright$, font=\color{yellow}, itemsep=2em]
\item \textbf{Flexible, robust and hierarchical} taxonomy;
\item \textbf{Fast, lightweight and modular} pipeline for model evaluation;
\item Baseline for geometric, image-based and height-based features;
\item More annotated data $\longrightarrow$ \textbf{Simulate errors} from the taxonomy based on reference data;
\item Need for features leveraging data structure $\longrightarrow$ Graph kernels, deep learning.
\end{itemize}
\uncover<2->{
~\\
Future work:
\begin{itemize}[label=$\blacktriangleright$, font=\color{purple}, itemsep=2em]
\item Dataset augmentation $\longrightarrow$ \textbf{Simulate errors} from the taxonomy based on reference data;
\item Extend to richer features $\longrightarrow$ Graph kernels, deep learning.
\end{itemize}
}
\end{frame}
\end{document}

0 comments on commit 97cc279

Please sign in to comment.