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); }