private void initLRA(Vector<double> firstFeatures, int featureCount)
{
threshold = Convert.ToDouble(epsilon.Text.Replace('.',','));
E = firstFeatures.ToColumnMatrix();
var m = 1 / firstFeatures.DotProduct(firstFeatures);
M = DenseMatrix.Create(1,1,m);
mask = null;
mask = new List<int>();
}
private void computeTransform()
{
Func<SkeletonPoint, Vector<double>> conv = (sp) => new DenseVector(new double[] { sp.X, sp.Y, sp.Z });
p0 = conv(dBlue.Value);
var p1 = conv(dRed.Value);
var p2 = conv(dYellow.Value);
f2 = (p1 - p0).Normalize(1);
f1 = (p2 - p0).Normalize(1);
f1 = (f1 - (f1.DotProduct(f2) * f2)).Normalize(1);
f3 = new DenseVector(new double[] { f1[1] * f2[2] - f1[2] * f2[1], f1[2] * f2[0] - f1[0] * f2[2], f1[0] * f2[1] - f1[1] * f2[0] });
f3 = f3.Normalize(1);
IsValid = true;
}