/// <summary>
/// This function determines a double value which ranks the likelyhood a point is part of this tracker.
/// Smaller numbers are more likely than larger ones. Distributions need all the data in order to be normalised with respect to another.
/// </summary>
/// <param name="pInput"></param>
/// <returns>A double word value which ranks the likelyhood of this input being part of this tracker. Smaller is better.</returns>
public double getClassificationRanking(SpatioTemporalInput pInput)
{
// TODO: TIME IS NOT TAKEN INTO ACCOUNT OF IN THESE EQUATIONS....
// Compute the distance of the input point to the best and predicted.
Vector vInput = pInput.Point;
double fDistanceFromBest = (Position - vInput).Length;
double fDistanceFromPredicted = (PredictedNextPosition - vInput).Length;
// Select the smallest of the two lengths (an optimistic algorythm).
return(Math.Min(fDistanceFromBest, fDistanceFromPredicted));
}
/// <summary>
/// Take an input which is gaurenteed to be part of this tracker. Update the tracker based on the input.
/// </summary>
/// <param name="pInput">The input we wish to consume.</param>
public void consumeInput(SpatioTemporalInput pInput)
{
// Add the point to the smoothing buffer.
this.SmoothingBuffer.addValue(pInput.Point);
// Compute the position as the newly smoothed value.
Vector tLastPosition = this.Position;
this.Position = this.SmoothingBuffer.getSmoothedValue();
// Compute the forward as the difference between the two.
Forward = new Vector(tLastPosition.X - this.Position.X, tLastPosition.Y - this.Position.Y);
// Compute the radius as the length of the next predicted.
//double fLength = Forward.Length * 10;
//fLength = 100;// Math.Max(50, Math.Min(fLength, 500));
//if (fLength == 0)
// fLength = 100.0f;
// Compute the normalised forward vector.
NormalForward = Forward;
NormalForward.Normalize();
// Now, if I were handling an adaptive radius, I would update it here to encompass the new predicted position.
//PredictionScale = fLength;
// If our tracker lock is 0 then it is sorta-safe to say we are the starting position.
if (iTrackerLock == 0)
{
StartPosition = Position;
}
// Increment the tracker lock and reset the lost lock to 0.
++iTrackerLock;
iTrackerLostLock = 0;
}
/// <summary>
/// Construct a new process pair. This will invoke 'getClassificationRanking' on the tracker.
/// </summary>
/// <param name="pTracker">The tracker to pair.</param>
/// <param name="pInput">The input to pair.</param>
public ProcessPair(SpatioTemporalTracker pTracker, SpatioTemporalInput pInput)
{
this.pInput = pInput;
this.pTracker = pTracker;
this.fRanking = pTracker.getClassificationRanking(this.pInput);
}
