コード例 #1
0
        /// <summary>
        ///   Creates an homography matrix matching points
        ///   from a set of points to another.
        /// </summary>
        public static MatrixH Homography(PointH[] points1, PointH[] points2)
        {
            // Initial argument checkings
            if (points1.Length != points2.Length)
            {
                throw new ArgumentException("The number of points should be equal.");
            }

            if (points1.Length < 4)
            {
                throw new ArgumentException("At least four points are required to fit an homography");
            }


            int N = points1.Length;

            MatrixH T1, T2; // Normalize input points

            points1 = points1.Normalize(out T1);
            points2 = points2.Normalize(out T2);

            // Create the matrix A
            double[,] A = new double[3 * N, 9];
            for (int i = 0; i < N; i++)
            {
                PointH X = points1[i];
                double x = points2[i].X;
                double y = points2[i].Y;
                double w = points2[i].W;
                int    r = 3 * i;

                A[r, 0] = 0;
                A[r, 1] = 0;
                A[r, 2] = 0;
                A[r, 3] = -w * X.X;
                A[r, 4] = -w * X.Y;
                A[r, 5] = -w * X.W;
                A[r, 6] = y * X.X;
                A[r, 7] = y * X.Y;
                A[r, 8] = y * X.W;

                r++;
                A[r, 0] = w * X.X;
                A[r, 1] = w * X.Y;
                A[r, 2] = w * X.W;
                A[r, 3] = 0;
                A[r, 4] = 0;
                A[r, 5] = 0;
                A[r, 6] = -x * X.X;
                A[r, 7] = -x * X.Y;
                A[r, 8] = -x * X.W;

                r++;
                A[r, 0] = -y * X.X;
                A[r, 1] = -y * X.Y;
                A[r, 2] = -y * X.W;
                A[r, 3] = x * X.X;
                A[r, 4] = x * X.Y;
                A[r, 5] = x * X.W;
                A[r, 6] = 0;
                A[r, 7] = 0;
                A[r, 8] = 0;
            }


            // Create the singular value decomposition
            SingularValueDecomposition svd = new SingularValueDecomposition(A, false, true);

            double[,] V = svd.RightSingularVectors;


            // Extract the homography matrix
            MatrixH H = new MatrixH((float)V[0, 8], (float)V[1, 8], (float)V[2, 8],
                                    (float)V[3, 8], (float)V[4, 8], (float)V[5, 8],
                                    (float)V[6, 8], (float)V[7, 8], (float)V[8, 8]);

            // Denormalize
            H = T2.Inverse().Multiply(H.Multiply(T1));

            return(H);
        }