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small changes in abstract and intro

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toni
2016-02-25 19:48:37 +01:00
parent a8b91b141d
commit 6ef06459cb
2 changed files with 3 additions and 3 deletions
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tex/chapters/abstract.tex
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@@ -6,6 +6,6 @@ In order to create such paths, we present a method that assigns an importance-fa
The human movement is then modelled by moving along adjacent nodes into the most proper walking-direction.
To enable 3D localisation, realistically shaped stairs for step-wise floor changes are used.
The position is estimated over multiple floors integrating different sensor modalities, namely Wi-Fi, iBeacons, barometer, step- and turn-detection.
The system was tested by omitting any time-consuming fingerprinting and calibration process and starts with a uniform distribution over the whole building instead of a well known pedestrian location.
The system was tested by avoiding any time-consuming fingerprinting and calibration process and starts with a uniform distribution over the whole building instead of a well known pedestrian location.
The evaluation shows that adding prior knowledge is able to improve the localisation, even under unpredictable behaviour, faulty measurements and poorly chosen system parameters.
\end{abstract}

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tex/chapters/introduction.tex
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@@ -37,8 +37,8 @@ Despite very good results, the system presented in \cite{Ebner-15} suffers from
First, the transition model of our previous approach uses discrete floor-changes.
Although the overall system provides viable results, it does not resemble real-world floor changes.
Especially the barometer is affected due to its continuous pressure measurements.
The discrete model prevents the barometer's full potential.
Especially the barometric model is affected due to its continuous pressure measurements.
The discrete model limits the barometer's full potential.
It could further be shown that a correct estimation strongly depends on the quality of $z$-transitions.
To address this problem we extended the graph by adding realistic stairs, allowing a step-wise transition in the $z$-direction.