public void ComputeK(List <DatasetFrame> fr)
{
Random rand = new Random();
int countFrame = Math.Min(MaxPairsForK, (int)Math.Ceiling(fr.Count * 0.1));
List <Mat> checkedFrames = new List <Mat>();
for (int c = 0; c < countFrame; c++)
{
int f = rand.Next(0, fr.Count - 1);
checkedFrames.Add(CvInvoke.Imread(fr[f].ImageFile, Emgu.CV.CvEnum.ImreadModes.Color).ToImage <Bgr, byte>().Mat);
checkedFrames.Add(CvInvoke.Imread(fr[f + 1].ImageFile, Emgu.CV.CvEnum.ImreadModes.Color).ToImage <Bgr, byte>().Mat);
}
double maxDistance = 20.0;
K = EstimateCameraFromImageSequence.K(checkedFrames, Detector, Descriptor, DistanceType, maxDistance);
}
public void ProcessImages(Mat left, Mat middle, Mat right, Feature2D detector, Feature2D descriptor, DistanceType distance)
{
double maxDistance = 20.0;
var match12 = MatchImagePair.Match(left, middle, detector, descriptor, distance, maxDistance);
var match23 = MatchImagePair.Match(middle, right, detector, descriptor, distance, maxDistance);
var match13 = MatchImagePair.Match(left, right, detector, descriptor, distance, maxDistance);
TripletMatch tmatch = new TripletMatch();
List <MDMatch> m12 = new List <MDMatch>();
List <MDMatch> m23 = new List <MDMatch>();
var left1 = match12.LeftPoints;
var right1 = match12.RightPoints;
var left2 = match23.LeftPoints;
var left2_X = MatchClosePoints.SortByX(match23.LeftPoints);
var right2 = match23.RightPoints;
var left3 = match13.LeftPoints;
var right3 = match13.RightPoints;
var right3_X = MatchClosePoints.SortByX(match13.LeftPoints);
for (int idx12 = 0; idx12 < left1.Size; ++idx12)
{
var p1 = left1[idx12];
var p2 = right1[idx12];
int idx23 = IndexOf_X(left2_X, p2);
if (idx23 != -1)
{
var p3 = right2[idx23];
int idx13 = IndexOf_X(right3_X, p1);
if (idx13 != -1)
{
if (AreEqual(left1[idx12], left3[idx13]))
{
tmatch.Left.Add(p1);
tmatch.Middle.Add(p2);
tmatch.Right.Add(p3);
m12.Add(match12.Matches[idx12]);
m23.Add(match23.Matches[idx23]);
}
}
}
}
match12.Matches = new VectorOfDMatch(m12.ToArray());
match23.Matches = new VectorOfDMatch(m23.ToArray());
MatchDrawer.DrawFeatures(left, right, match12, 1.0, bottomView);
MatchDrawer.DrawFeatures(left, right, match23, 1.0, upperView);
var F12 = ComputeMatrix.F(new VectorOfPointF(tmatch.Left.ToArray()), new VectorOfPointF(tmatch.Middle.ToArray()));
var F23 = ComputeMatrix.F(new VectorOfPointF(tmatch.Middle.ToArray()), new VectorOfPointF(tmatch.Right.ToArray()));
var F13 = ComputeMatrix.F(new VectorOfPointF(tmatch.Left.ToArray()), new VectorOfPointF(tmatch.Right.ToArray()));
if (F12 == null || F23 == null || F13 == null)
{
info.Text = "Too few matches";
return;
}
var Fs = new List <Image <Arthmetic, double> > {
F12, F23, F13
};
var K = EstimateCameraFromImageSequence.K(Fs, left.Width, right.Height);
var Es = new List <Image <Arthmetic, double> >
{
ComputeMatrix.E(F12, K),
ComputeMatrix.E(F23, K),
ComputeMatrix.E(F13, K)
};
FindTransformation.DecomposeToRTAndTriangulate(tmatch.Left, tmatch.Middle, K, Es[0],
out Image <Arthmetic, double> R12, out Image <Arthmetic, double> t12, out Image <Arthmetic, double> X12);
FindTransformation.DecomposeToRTAndTriangulate(tmatch.Middle, tmatch.Right, K, Es[1],
out Image <Arthmetic, double> R23, out Image <Arthmetic, double> t23, out Image <Arthmetic, double> X23);
FindTransformation.DecomposeToRTAndTriangulate(tmatch.Left, tmatch.Right, K, Es[2],
out Image <Arthmetic, double> R13, out Image <Arthmetic, double> t13, out Image <Arthmetic, double> X13);
var Rs = new List <Image <Arthmetic, double> >
{
RotationConverter.MatrixToEulerXYZ(R12),
RotationConverter.MatrixToEulerXYZ(R23),
RotationConverter.MatrixToEulerXYZ(R13)
};
var ts = new List <Image <Arthmetic, double> >
{
t12,
t23,
t13
};
PrintMatricesInfo(Es, K, Rs, ts);
}