Added the Protractor algorithm for calculating the minimum cosine distance between gestures (4758f121) · Commits · e / os / android_frameworks_base

core/java/android/gesture/GestureStore.java

+6 −1

Original line number	Diff line number	Diff line
		@@ -65,7 +65,12 @@ public class GestureStore {

		// ORIENTATION_SENSITIVE and ORIENTATION_INVARIANT are only for SEQUENCE_SENSITIVE gestures
		public static final int ORIENTATION_INVARIANT = 1;
		// at most 2 directions can be recognized
		public static final int ORIENTATION_SENSITIVE = 2;
		// at most 4 directions can be recognized
		static final int ORIENTATION_SENSITIVE_4 = 4;
		// at most 8 directions can be recognized
		static final int ORIENTATION_SENSITIVE_8 = 8;

		private static final short FILE_FORMAT_VERSION = 1;

		@@ -131,7 +136,7 @@ public class GestureStore {
		public ArrayList<Prediction> recognize(Gesture gesture) {
		Instance instance = Instance.createInstance(mSequenceType,
		mOrientationStyle, gesture, null);
		return mClassifier.classify(mSequenceType, instance.vector);
		return mClassifier.classify(mSequenceType, mOrientationStyle, instance.vector);
		}

		/**

+32 −0

Original line number	Diff line number	Diff line
		@@ -367,6 +367,38 @@ final class GestureUtilities {
		return Math.acos(sum);
		}

		/**
		* Calculate the "minimum" cosine distance between two instances
		*
		* @param vector1
		* @param vector2
		* @param numOrientations the maximum number of orientation allowed
		* @return the distance between the two instances (between 0 and Math.PI)
		*/
		static double minimumCosineDistance(float[] vector1, float[] vector2, int numOrientations) {
		final int len = vector1.length;
		double a = 0;
		double b = 0;
		for (int i = 0; i < len; i += 2) {
		a += vector1[i] * vector2[i] + vector1[i + 1] * vector2[i + 1];
		b += vector1[i] * vector2[i + 1] - vector1[i + 1] * vector2[i];
		}
		if (a != 0) {
		final double tan = b/a;
		final double angle = Math.atan(tan);
		if (numOrientations > 2 && Math.abs(angle) >= Math.PI / numOrientations) {
		return Math.acos(a);
		} else {
		final double cosine = Math.cos(angle);
		final double sine = cosine * tan;
		return Math.acos(a * cosine + b * sine);
		}
		} else {
		return Math.PI / 2;
		}
		}


		static OrientedBoundingBox computeOrientedBoundingBox(ArrayList<GesturePoint> pts) {
		GestureStroke stroke = new GestureStroke(pts);
		float[] points = temporalSampling(stroke, TEMPORAL_SAMPLING_RATE);

+1 −1

Original line number	Diff line number	Diff line
		@@ -94,7 +94,7 @@ class Instance {
		float orientation = (float)Math.atan2(pts[1] - center[1], pts[0] - center[0]);

		float adjustment = -orientation;
		if (orientationType == GestureStore.ORIENTATION_SENSITIVE) {
		if (orientationType != GestureStore.ORIENTATION_INVARIANT) {
		int count = ORIENTATIONS.length;
		for (int i = 0; i < count; i++) {
		float delta = ORIENTATIONS[i] - orientation;

+2 −2

Original line number	Diff line number	Diff line
		@@ -41,7 +41,7 @@ class InstanceLearner extends Learner {
		};

		@Override
		ArrayList<Prediction> classify(int sequenceType, float[] vector) {
		ArrayList<Prediction> classify(int sequenceType, int orientationType, float[] vector) {
		ArrayList<Prediction> predictions = new ArrayList<Prediction>();
		ArrayList<Instance> instances = getInstances();
		int count = instances.size();
		@@ -53,7 +53,7 @@ class InstanceLearner extends Learner {
		}
		double distance;
		if (sequenceType == GestureStore.SEQUENCE_SENSITIVE) {
		distance = GestureUtilities.cosineDistance(sample.vector, vector);
		distance = GestureUtilities.minimumCosineDistance(sample.vector, vector, orientationType);
		} else {
		distance = GestureUtilities.squaredEuclideanDistance(sample.vector, vector);
		}

+1 −1

Original line number	Diff line number	Diff line
		@@ -79,5 +79,5 @@ abstract class Learner {
		instances.removeAll(toDelete);
		}

		abstract ArrayList<Prediction> classify(int gestureType, float[] vector);
		abstract ArrayList<Prediction> classify(int sequenceType, int orientationType, float[] vector);
		}