private float Correct(double value, ref KalmanFilter filter)
{
if (filter == null)
{
filter = factory.Create();
}
var corrected = new float[2, 1];
var measurement = new Matrix<float>(1, 1)
{
[0, 0] = (float) value
};
public KalmanFilter Create()
{
var filter = new KalmanFilter(2, 1, 0);
transitionMatrix.Mat.CopyTo(filter.TransitionMatrix);
measurementMatrix.SetIdentity();
measurementMatrix.Mat.CopyTo(filter.MeasurementMatrix);
processNoiseCov.SetIdentity(new MCvScalar(1.0e-5));
processNoiseCov.Mat.CopyTo(filter.ProcessNoiseCov);
measurementNoiseCov.SetIdentity(new MCvScalar(1.0e-2));
measurementNoiseCov.Mat.CopyTo(filter.MeasurementNoiseCov);
errorCovPost.SetIdentity();
errorCovPost.Mat.CopyTo(filter.ErrorCovPost);
filter.StatePost.SetTo(new float[] {0, 0});
return filter;
}
//[Test]
public void TestKalman()
{
Image<Bgr, Byte> img = new Image<Bgr, byte>(400, 400);
SyntheticData syntheticData = new SyntheticData();
//Matrix<float> state = new Matrix<float>(new float[] { 0.0f, 0.0f}); //initial guess
#region initialize Kalman filter
KalmanFilter tracker = new KalmanFilter(2, 1, 0);
syntheticData.TransitionMatrix.Mat.CopyTo(tracker.TransitionMatrix);
syntheticData.MeasurementMatrix.Mat.CopyTo(tracker.MeasurementMatrix);
syntheticData.ProcessNoise.Mat.CopyTo(tracker.ProcessNoiseCov);
syntheticData.MeasurementNoise.Mat.CopyTo(tracker.MeasurementNoiseCov);
syntheticData.ErrorCovariancePost.Mat.CopyTo(tracker.ErrorCovPost);
tracker.StatePost.SetTo(new float[] { 0.0f, 0.0f });
#endregion
System.Converter<double, PointF> angleToPoint =
delegate(double radianAngle)
{
return new PointF(
(float)(img.Width / 2 + img.Width / 3 * Math.Cos(radianAngle)),
(float)(img.Height / 2 - img.Width / 3 * Math.Sin(radianAngle)));
};
Action<PointF, Bgr> drawCross =
delegate(PointF point, Bgr color)
{
img.Draw(new Cross2DF(point, 15, 15), color, 1);
};
ImageViewer viewer = new ImageViewer();
System.Windows.Forms.Timer timer = new System.Windows.Forms.Timer();
timer.Interval = 200;
timer.Tick += new EventHandler(delegate(object sender, EventArgs e)
{
Matrix<float> measurement = syntheticData.GetMeasurement();
// adjust Kalman filter state
tracker.Correct(measurement.Mat);
tracker.Predict();
#region draw the state, prediction and the measurement
float[] correctedState = new float[2];
float[] predictedState = new float[2];
tracker.StatePost.CopyTo(correctedState);
tracker.StatePre.CopyTo(predictedState);
PointF statePoint = angleToPoint(correctedState[0]);
PointF predictPoint = angleToPoint(predictedState[0]);
PointF measurementPoint = angleToPoint(measurement[0, 0]);
img.SetZero(); //clear the image
drawCross(statePoint, new Bgr(Color.White)); //draw current state in White
drawCross(measurementPoint, new Bgr(Color.Red)); //draw the measurement in Red
drawCross(predictPoint, new Bgr(Color.Green)); //draw the prediction (the next state) in green
img.Draw(new LineSegment2DF(statePoint, predictPoint), new Bgr(Color.Magenta), 1); //Draw a line between the current position and prediction of next position
//Trace.WriteLine(String.Format("Velocity: {0}", tracker.CorrectedState[1, 0]));
#endregion
syntheticData.GoToNextState();
viewer.Image = img;
});
timer.Start();
viewer.Disposed += delegate(Object sender, EventArgs e) { timer.Stop(); };
viewer.Text = "Actual State: White; Measurement: Red; Prediction: Green";
viewer.ShowDialog();
}