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Captions & performance bla bla

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MBulli
2018-02-26 18:49:23 +01:00
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tex/chapters/realworld.tex
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@@ -17,14 +17,14 @@ The bivariate state estimation was calculated whenever a step was recognized, ab
\begin{figure}
\input{gfx/walk.tex}
\caption{Occurring bimodal distribution, caused by uncertain measurements. After \SI{20.8}{\second}, the distribution gets unimodal. The weigted-average estimation (blue) provides an high error compared to the ground truth (solid black), while the boxKDE approach (green) does not. }
\caption{Occurring bimodal distribution, caused by uncertain measurements. After \SI{20.8}{\second}, the distribution gets unimodal. The weigted-average estimation (blue) provides an high error compared to the ground truth (solid black), while the boxKDE approach (orange) does not. }
\label{fig:realWorldMulti}
\end{figure}
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Fig. \ref{fig:realWorldMulti} illustrates a frequently occurring situation, where the particle set splits apart, due to uncertain measurements and multiple possible walking directions.
This results in a bimodal posterior distribution, which reaches its maximum distances between the modes at \SI{13.4}{\second} (black dotted line).
Thus estimating the most probable state using the weighted-average results in the blue line, describing the pedestrian's position to be somewhere outside the building (light green area).
In contrast, the here proposed method (green line) is able to retrieve a good estimate compared the the ground truth path shown by the black solid line.
In contrast, the here proposed method (orange line) is able to retrieve a good estimate compared the the ground truth path shown by the black solid line.
Due to a right turn, the distribution gets unimodal after \SI{20.8}{\second}.
This happens since the lower red particles are walking against a wall and thus punished with a low weight.