Classifier class van wiigee toegevoegd, deze was op mysterieuze wijze verdwenen waardoor fouten optraden.

java/src/org/wiigee/logic/Classifier.java

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+/*
+ * wiigee - accelerometerbased gesture recognition
+ * Copyright (C) 2007, 2008, 2009 Benjamin Poppinga
+ * 
+ * Developed at University of Oldenburg
+ * Contact: wiigee@benjaminpoppinga.de
+ *
+ * This file is part of wiigee.
+ *
+ * wiigee is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU Lesser General Public License as published by
+ * the Free Software Foundation; either version 2 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU Lesser General Public License for more details.
+ * 
+ * You should have received a copy of the GNU Lesser General Public License along
+ * with this program; if not, write to the Free Software Foundation, Inc.,
+ * 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
+ */
+
+package org.wiigee.logic;
+
+import java.util.Vector;
+
+public class Classifier {
+
+	private Vector<GestureModel> gesturemodel; // each gesturetype got its own 
+										// gesturemodel in this vector
+	private double lastprob;
+	
+	public Classifier() {
+		this.gesturemodel=new Vector<GestureModel>();
+		this.lastprob=0.0;
+	}
+	
+	/** 
+	 * This method recognize a specific gesture, given to the procedure.
+	 * For classification a bayes classification algorithm is used.
+	 * 
+	 * @param g	gesture to classify
+	 */
+	public int classifyGesture(Gesture g) {
+		//Log.write("Recognizing gesture...");
+		
+		// Wert im Nenner berechnen, nach Bayes
+		double sum = 0;
+		for(int i=0; i<this.gesturemodel.size(); i++) {
+			sum+=this.gesturemodel.elementAt(i).getDefaultProbability()*
+					this.gesturemodel.elementAt(i).matches(g);
+		}
+		
+		int recognized = -1; // which gesture has been recognized
+		double recogprob = Integer.MIN_VALUE; // probability of this gesture
+		double probgesture = 0; // temporal value for bayes algorithm
+		double probmodel = 0; // temporal value for bayes algorithm
+		for(int i=0; i<this.gesturemodel.size(); i++) {
+			//this.gesturemodel.elementAt(i).print(); // Debug
+			double tmpgesture = this.gesturemodel.elementAt(i).matches(g);
+			double tmpmodel = this.gesturemodel.elementAt(i).getDefaultProbability();
+			
+			if(((tmpmodel*tmpgesture)/sum)>recogprob) {
+				probgesture=tmpgesture;
+				probmodel=tmpmodel;
+				recogprob=((tmpmodel*tmpgesture)/sum);
+				recognized=i;
+			}
+		}
+		
+		// a gesture could be recognized
+		if(recogprob>0 && probmodel>0 && probgesture>0 && sum>0) {
+			this.lastprob=recogprob;
+			return recognized;
+		} else {
+			// no gesture could be recognized
+			return -1;
+		}
+		
+	}
+	
+	public double getLastProbability() {
+		return this.lastprob;
+	}
+	
+	public void addGestureModel(GestureModel gm) {
+		this.gesturemodel.add(gm);
+	}
+
+	public GestureModel getGestureModel(int id) {
+		return this.gesturemodel.elementAt(id);
+	}
+	
+	public Vector<GestureModel> getGestureModels() {
+		return this.gesturemodel;
+	}
+
+    public int getCountOfGestures() {
+        return this.gesturemodel.size();
+    }
+	
+	public void clear() {
+		this.gesturemodel = new Vector<GestureModel>();
+	}
+	
+
+}