Exemplo n.º 1
0
        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);
        }