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Extended qualitative analysis

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Signed-off-by: Jim Martens <github@2martens.de>
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Jim Martens
2019-09-18 13:28:10 +02:00
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@ -853,15 +853,42 @@ similarities and differences between both approaches. For this
comparison, 0.2 confidence threshold is applied. Furthermore, Bayesian
SSD uses non-maximum suppression and dropout with 0.9 keep ratio.
\begin{figure}[ht]
\centering
\includegraphics[width=0.5\textwidth]{COCO_val2014_000000336587}
\caption{Image with stop sign and a truck at the right edge. Origin of the image is the top left corner.}
\label{fig:stop-sign-truck}
\begin{figure}
\begin{minipage}[t]{0.48\textwidth}
\includegraphics[width=\textwidth]{COCO_val2014_000000336587_bboxes_vanilla}
\caption{Image with stop sign and truck at right edge. Ground truth in blue and predictions in red. Predictions are from vanilla SSD.}
\label{fig:stop-sign-truck-vanilla}
\end{minipage}%
\hfill
\begin{minipage}[t]{0.48\textwidth}
\includegraphics[width=\textwidth]{COCO_val2014_000000336587_bboxes_bayesian}
\caption{Image with stop sign and truck at right edge. Ground truth in blue and predictions in red. Predictions are from Bayesian SSD with 0.9 keep ratio.}
\label{fig:stop-sign-truck-bayesian}
\end{minipage}
\end{figure}
In the ground truth, only a stop sign and a truck are detected in figure \ref{fig:stop-sign-truck}. The truck is neither detected by vanilla nor Bayesian SSD. Instead both detected a pottet plant and a traffic light.
The stop sign is detected by both variants.
In the ground truth, only a stop sign and a truck are detected. The differences between vanilla SSD and Bayesian SSD are almost not visible
(see figures \ref{fig:stop-sign-truck-vanilla} and \ref{fig:stop-sign-truck-bayesian}). The truck is neither detected by vanilla nor Bayesian SSD. Instead both detected a pottet plant and a traffic light. The stop sign is detected by both variants.
This behaviour implies problems with detecting objects at the edge
that overwhelmingly lie outside the image frame. Furthermore, the predictions are usually identical - when rounding to three digits.
\begin{figure}
\begin{minipage}[t]{0.48\textwidth}
\includegraphics[width=\textwidth]{COCO_val2014_000000403817_bboxes_vanilla}
\caption{Image with a cat and laptop/TV. Ground truth in blue and predictions in red. Predictions are from vanilla SSD.}
\label{fig:cat-laptop-vanilla}
\end{minipage}%
\hfill
\begin{minipage}[t]{0.48\textwidth}
\includegraphics[width=\textwidth]{COCO_val2014_000000403817_bboxes_bayesian}
\caption{Image with a cat and laptop/TV. Ground truth in blue and predictions in red. Predictions are from Bayesian SSD with 0.9 keep ratio.}
\label{fig:cat-laptop-bayesian}
\end{minipage}
\end{figure}
Another example (see figures \ref{fig:cat-laptop-vanilla} and \ref{fig:cat-laptop-bayesian}) is a cat with a laptop/TV in the background on the right
side. Both variants detect a cat but the vanilla variant detects a dog as well. The laptop and TV are not detected but this is expected since
the classes were not trained.
\chapter{Discussion and Outlook}