First version of activity paragraph

tex/chapters/filtering.tex

@@ -93,5 +93,17 @@
 			%
 			
 		\subsection{Activity-Detection}
-			\todo{write}
+			% Activity Recognition
+			% Naives Bayes als Klassifikator
+			% Features -> 1: Variance of mean 2: Differenz zwischen Barometer
+			% Zeitintervall für das die Merkmale berechnet werden
+			
+			The transition model includes a simple recognizer of different locomotion modes like normal walking or ascending/descending stairs. The reasoning behind this is to favour paths that correspond with the detected locomotion mode. 
+			
+			We use a Naives Bayes classifier with two features. For this, the sensor signals are split in sliding windows. Each window has a length of one second and overlaps 500 ms with its prior window.  
+			The first feature is the variance of the accelerometer's magnitude during a window and the second feature is the difference between the last and first barometer measurement of the particular window.
+			Based on these features the classifier assigns an activity to each sliding window.
+			  
+			
+			\todo{Was passiert wenn ein überlappendes Fenster zwei verschiedene Aktivitäten zugewiesen bekommt? Sliding windows evtl. weglassen?}