/// <summary>
///
/// </summary>
/// <param name="m1"></param>
/// <param name="m2"></param>
/// <param name="model"></param>
/// <param name="maxIters"></param>
/// <returns></returns>
public override unsafe bool Refine(CvMat m1, CvMat m2, CvMat model, int maxIters)
{
CvLevMarq solver = new CvLevMarq(8, 0, new CvTermCriteria(maxIters, double.Epsilon));
int count = m1.Rows * m1.Cols;
CvPoint2D64f *M = (CvPoint2D64f *)m1.DataByte;
CvPoint2D64f *m = (CvPoint2D64f *)m2.DataByte;
CvMat modelPart = new CvMat(solver.Param.Rows, solver.Param.Cols, model.ElemType, model.Data);
Cv.Copy(modelPart, solver.Param);
for (; ;)
{
CvMat _param = null;
CvMat _JtJ = null, _JtErr = null;
double _errNorm = 0;
if (!solver.UpdateAlt(out _param, out _JtJ, out _JtErr, out _errNorm))
{
break;
}
for (int i = 0; i < count; i++)
{
double * h = _param.DataDouble;
double Mx = M[i].X, My = M[i].Y;
double ww = 1.0 / (h[6] * Mx + h[7] * My + 1.0);
double _xi = (h[0] * Mx + h[1] * My + h[2]) * ww;
double _yi = (h[3] * Mx + h[4] * My + h[5]) * ww;
double[] err = { _xi - m[i].X, _yi - m[i].Y };
if (_JtJ != null || _JtErr != null)
{
double[,] J = new double[2, 8]
{
{ Mx *ww, My *ww, ww, 0, 0, 0, -Mx *ww *_xi, -My *ww *_xi },
{ 0, 0, 0, Mx *ww, My *ww, ww, -Mx * ww * _yi, -My * ww * _yi }
};
for (int j = 0; j < 8; j++)
{
for (int k = j; k < 8; k++)
{
_JtJ.DataDouble[j * 8 + k] += J[0, j] * J[0, k] + J[1, j] * J[1, k];
}
_JtErr.DataDouble[j] += J[0, j] * err[0] + J[1, j] * err[1];
}
}
if (_errNorm != 0)
{
solver.ErrNorm += err[0] * err[0] + err[1] * err[1];
}
}
}
Cv.Copy(solver.Param, modelPart);
return(true);
}
/// <summary>
///
/// </summary>
/// <param name="m1"></param>
/// <param name="m2"></param>
/// <param name="model"></param>
/// <param name="maxIters"></param>
/// <returns></returns>
public override unsafe bool Refine(CvMat m1, CvMat m2, CvMat model, int maxIters)
{
CvLevMarq solver = new CvLevMarq(8, 0, new CvTermCriteria(maxIters, double.Epsilon));
int count = m1.Rows * m1.Cols;
CvPoint2D64f* M = (CvPoint2D64f*)m1.DataByte;
CvPoint2D64f* m = (CvPoint2D64f*)m2.DataByte;
CvMat modelPart = new CvMat(solver.Param.Rows, solver.Param.Cols, model.ElemType, model.Data);
Cv.Copy(modelPart, solver.Param);
for (; ; )
{
CvMat _param = null;
CvMat _JtJ = null, _JtErr = null;
double _errNorm = 0;
if (!solver.UpdateAlt(out _param, out _JtJ, out _JtErr, out _errNorm))
break;
for (int i = 0; i < count; i++)
{
double* h = _param.DataDouble;
double Mx = M[i].X, My = M[i].Y;
double ww = 1.0 / (h[6] * Mx + h[7] * My + 1.0);
double _xi = (h[0] * Mx + h[1] * My + h[2]) * ww;
double _yi = (h[3] * Mx + h[4] * My + h[5]) * ww;
double[] err = { _xi - m[i].X, _yi - m[i].Y };
if (_JtJ != null || _JtErr != null)
{
double[,] J = new double[2, 8]
{
{ Mx*ww, My*ww, ww, 0, 0, 0, -Mx*ww*_xi, -My*ww*_xi },
{ 0, 0, 0, Mx*ww, My*ww, ww, -Mx*ww*_yi, -My*ww*_yi }
};
for (int j = 0; j < 8; j++)
{
for (int k = j; k < 8; k++)
_JtJ.DataDouble[j * 8 + k] += J[0, j] * J[0, k] + J[1, j] * J[1, k];
_JtErr.DataDouble[j] += J[0, j] * err[0] + J[1, j] * err[1];
}
}
if (_errNorm != 0)
solver.ErrNorm += err[0] * err[0] + err[1] * err[1];
}
}
Cv.Copy(solver.Param, modelPart);
return true;
}
/// <summary>
/// 既知の内部パラメータを用いて，それぞれのビューにおける外部パラメータを推定する．
/// 3次元のオブジェクトの点とそれに対応する２次元投影点が指定されなければならない．この関数も逆投影誤差の最小化を行う．
/// </summary>
/// <param name="objectPoints">オブジェクトの点の配列．3xNまたはNx3でNはビューにおける点の数．</param>
/// <param name="imagePoints">対応する画像上の点の配列．2xNまたはNx2でNはビューにおける点の数．</param>
/// <param name="cameraMatrix">カメラ内部行列 (A) [fx 0 cx; 0 fy cy; 0 0 1]. </param>
/// <param name="distCoeffs">歪み係数のベクトル．4x1または1x4 [k1, k2, p1, p2]．nullの場合，歪み係数はすべて0 であるとする．</param>
/// <param name="rvec">出力される 3x1 の回転ベクトル</param>
/// <param name="tvec">出力される 3x1 の並進ベクトル</param>
/// <param name="useExtrinsicGuess"></param>
#else
/// <summary>
/// Finds extrinsic camera parameters for particular view
/// </summary>
/// <param name="objectPoints">The array of object points, 3xN or Nx3, where N is the number of points in the view. </param>
/// <param name="imagePoints">The array of corresponding image points, 2xN or Nx2, where N is the number of points in the view. </param>
/// <param name="cameraMatrix">The camera matrix (A) [fx 0 cx; 0 fy cy; 0 0 1]. </param>
/// <param name="distCoeffs">The vector of distortion coefficients, 4x1 or 1x4 [k1, k2, p1, p2]. If it is NULL, all distortion coefficients are considered 0's. </param>
/// <param name="rvec">The output 3x1 or 1x3 rotation vector (compact representation of a rotation matrix, see cvRodrigues2). </param>
/// <param name="tvec">The output 3x1 or 1x3 translation vector. </param>
/// <param name="useExtrinsicGuess"></param>
#endif
public static void FindExtrinsicCameraParams2Cs(CvMat objectPoints, CvMat imagePoints, CvMat cameraMatrix, CvMat distCoeffs, CvMat rvec, CvMat tvec, bool useExtrinsicGuess)
{
if (objectPoints == null)
throw new ArgumentNullException("objectPoints");
if (imagePoints == null)
throw new ArgumentNullException("imagePoints");
if (cameraMatrix == null)
throw new ArgumentNullException("cameraMatrix");
if (rvec == null)
throw new ArgumentNullException("rvec");
if (tvec == null)
throw new ArgumentNullException("tvec");
//IntPtr distCoeffsPtr = ToPtr(distCoeffs);
unsafe
{
const int maxIter = 20;
double[] ar = new double[9] { 1, 0, 0, 0, 1, 0, 0, 0, 1 };
double[] MM = new double[9],
U = new double[9],
V = new double[9],
W = new double[3];
double* param = stackalloc double[6];
CvMat matA = new CvMat(3, 3, MatrixType.F64C1);
CvMat _Ar = new CvMat(3, 3, MatrixType.F64C1, ar);
CvMat matR = new CvMat(3, 3, MatrixType.F64C1);
CvMat _r = new CvMat(3, 1, MatrixType.F64C1, new IntPtr(param));
CvMat _t = new CvMat(3, 1, MatrixType.F64C1, new IntPtr(param + 3));
CvMat _Mc = new CvMat(1, 3, MatrixType.F64C1);
CvMat _MM = new CvMat(3, 3, MatrixType.F64C1, MM);
CvMat matU = new CvMat(3, 3, MatrixType.F64C1, U);
CvMat matV = new CvMat(3, 3, MatrixType.F64C1, V);
CvMat matW = new CvMat(3, 1, MatrixType.F64C1, W);
CvMat _param = new CvMat(6, 1, MatrixType.F64C1, new IntPtr(param));
CvMat _dpdr, _dpdt;
if (!IS_MAT(objectPoints.CvPtr) ||
!IS_MAT(imagePoints.CvPtr) ||
!IS_MAT(cameraMatrix.CvPtr) ||
!IS_MAT(rvec.CvPtr) ||
!IS_MAT(tvec.CvPtr))
{
throw new ArgumentException();
}
int count = Math.Max(objectPoints.Cols, objectPoints.Rows);
CvMat matM = new CvMat(1, count, MatrixType.F64C3);
CvMat _m = new CvMat(1, count, MatrixType.F64C2);
ConvertPointsHomogeneous(objectPoints, matM);
ConvertPointsHomogeneous(imagePoints, _m);
Convert(cameraMatrix, matA);
if (!((rvec.ElemType == MatrixType.F64C1 || rvec.ElemType == MatrixType.F32C1) &&
(rvec.Rows == 1 || rvec.Cols == 1) && rvec.Rows * rvec.Cols * rvec.ElemChannels == 3))
{
throw new ArgumentException();
}
if (!((tvec.ElemType == MatrixType.F64C1 || tvec.ElemType == MatrixType.F32C1) &&
(tvec.Rows == 1 || tvec.Cols == 1) && tvec.Rows * tvec.Cols * tvec.ElemChannels == 3))
{
throw new ArgumentException();
}
CvMat _mn = new CvMat(1, count, MatrixType.F64C2);
CvMat _Mxy = new CvMat(1, count, MatrixType.F64C2);
// normalize image points
// (unapply the intrinsic matrix transformation and distortion)
UndistortPoints_(_m, _mn, matA, distCoeffs, null, _Ar);
if (useExtrinsicGuess)
{
using (CvMat _r_temp = new CvMat(rvec.Rows, rvec.Cols, MatrixType.F64C1))
using (CvMat _t_temp = new CvMat(tvec.Rows, tvec.Cols, MatrixType.F64C1))
{
Convert(rvec, _r_temp);
Convert(tvec, _t_temp);
for (int i = 0; i < Math.Max(rvec.Rows, rvec.Cols); i++)
{
param[i] = _r_temp.GetReal1D(i);
param[i + 3] = _t_temp.GetReal1D(i);
}
}
}
else
{
CvScalar Mc = Avg(matM);
_Mc[0] = Mc.Val0;
_Mc[1] = Mc.Val1;
_Mc[2] = Mc.Val2;
Reshape(matM, matM, 1, count);
MulTransposed(matM, _MM, true, _Mc);
SVD(_MM, matW, null, matV, SVDFlag.ModifyA | SVDFlag.V_T);
// initialize extrinsic parameters
if (W[2] / W[1] < 1e-3 || count < 4)
{
// a planar structure case (all M's lie in the same plane)
double[] h = new double[9];
CvMat R_transform = matV;
CvMat T_transform = new CvMat(3, 1, MatrixType.F64C1);
CvMat matH = new CvMat(3, 3, MatrixType.F64C1, h);
CvMat _h1, _h2, _h3;
if (V[2] * V[2] + V[5] * V[5] < 1e-10)
SetIdentity(R_transform);
if (Det(R_transform) < 0)
Scale(R_transform, R_transform, -1);
//GEMM(R_transform, _Mc, -1, null, 0, T_transform, GemmOperation.B_T);
for (int r = 0; r < 3; r++)
{
for (int c = 0; c < 1; c++)
{
double sum = 0;
for (int k = 0; k < 3; k++)
{
sum += R_transform.GetReal2D(r, k) * _Mc.GetReal2D(c, k);
}
T_transform.SetReal2D(r, c, sum * -1);
}
}
for (int i = 0; i < count; i++)
{
double* Rp = R_transform.DataDouble;
double* Tp = T_transform.DataDouble;
double* src = matM.DataDouble + i * 3;
double* dst = _Mxy.DataDouble + i * 2;
dst[0] = Rp[0] * src[0] + Rp[1] * src[1] + Rp[2] * src[2] + Tp[0];
dst[1] = Rp[3] * src[0] + Rp[4] * src[1] + Rp[5] * src[2] + Tp[1];
}
FindHomography_(_Mxy, _mn, matH);
GetCol(matH, out _h1, 0);
GetCol(matH, out _h2, 0);
GetCol(matH, out _h3, 0);
_h2.DataDouble += 1;
_h3.DataDouble += 2;
double h1_norm = Math.Sqrt(h[0] * h[0] + h[3] * h[3] + h[6] * h[6]);
double h2_norm = Math.Sqrt(h[1] * h[1] + h[4] * h[4] + h[7] * h[7]);
Scale(_h1, _h1, 1.0 / h1_norm);
Scale(_h2, _h2, 1.0 / h2_norm);
Scale(_h3, _t, 2.0 / (h1_norm + h2_norm));
CrossProduct(_h1, _h2, _h3);
Rodrigues2_(matH, _r);
Rodrigues2_(_r, matH);
MatMulAdd(matH, T_transform, _t, _t);
MatMul(matH, R_transform, matR);
Rodrigues2_(matR, _r);
}
else
{
// non-planar structure. Use DLT method
double[] LL = new double[12 * 12],
LW = new double[12],
LV = new double[12 * 12];
CvMat _LL = new CvMat(12, 12, MatrixType.F64C1, LL);
CvMat _LW = new CvMat(12, 1, MatrixType.F64C1, LW);
CvMat _LV = new CvMat(12, 12, MatrixType.F64C1, LV);
CvMat _RR, _tt;
CvPoint3D64f* M = (CvPoint3D64f*)matM.DataDouble;
CvPoint2D64f* mn = (CvPoint2D64f*)_mn.DataDouble;
CvMat matL = new CvMat(2 * count, 12, MatrixType.F64C1);
double* L = matL.DataDouble;
for (int i = 0; i < count; i++, L += 24)
{
double x = -mn[i].X, y = -mn[i].Y;
L[0] = L[16] = M[i].X;
L[1] = L[17] = M[i].Y;
L[2] = L[18] = M[i].Z;
L[3] = L[19] = 1.0;
L[4] = L[5] = L[6] = L[7] = 0.0;
L[12] = L[13] = L[14] = L[15] = 0.0;
L[8] = x * M[i].X;
L[9] = x * M[i].Y;
L[10] = x * M[i].Z;
L[11] = x;
L[20] = y * M[i].X;
L[21] = y * M[i].Y;
L[22] = y * M[i].Z;
L[23] = y;
}
MulTransposed(matL, _LL, true);
SVD(_LL, _LW, null, _LV, SVDFlag.ModifyA | SVDFlag.V_T);
double[] LV12 = new double[12];
Array.Copy(LV, 11 * 12, LV12, 0, 12);
CvMat _RRt = new CvMat(3, 4, MatrixType.F64C1, LV12);
GetCols(_RRt, out _RR, 0, 3);
GetCol(_RRt, out _tt, 3);
if (Det(_RR) < 0)
Scale(_RRt, _RRt, -1);
double sc = Norm(_RR);
SVD(_RR, matW, matU, matV, SVDFlag.ModifyA | SVDFlag.U_T | SVDFlag.V_T);
GEMM(matU, matV, 1, null, 0, matR, GemmOperation.A_T);
Scale(_tt, _t, Norm(matR) / sc);
Rodrigues2_(matR, _r);
}
}
Cv.Reshape(matM, matM, 3, 1);
Cv.Reshape(_mn, _mn, 2, 1);
// refine extrinsic parameters using iterative algorithm
CvLevMarq solver = new CvLevMarq(6, count * 2, new CvTermCriteria(maxIter, float.Epsilon), true);
Copy(_param, solver.Param);
/*
Console.WriteLine("matM-----");
for (int i = 0; i < matM.Rows * matM.Cols; i++)
{
Console.WriteLine("{0}\t", matM[i].Val0);
}
Console.WriteLine("_mn-----");
for (int i = 0; i < _mn.Rows * _mn.Cols; i++)
{
Console.WriteLine(_mn[i].Val0);
}
Console.WriteLine("_param-----");
for (int i = 0; i < _param.Rows * _param.Cols; i++)
{
Console.WriteLine(_param[i].Val0);
}*/
for (; ; )
{
CvMat matJ, _err, __param;
bool proceed = solver.Update(out __param, out matJ, out _err);
Copy(__param, _param);
if (!proceed || _err == null)
break;
Reshape(_err, _err, 2, 1);
if (matJ != null)
{
GetCols(matJ, out _dpdr, 0, 3);
GetCols(matJ, out _dpdt, 3, 6);
ProjectPoints2(matM, _r, _t, matA, distCoeffs,
_err, _dpdr, _dpdt, null, null, null);
}
else
{
ProjectPoints2(matM, _r, _t, matA, distCoeffs, _err, null, null, null, null, null);
}
Sub(_err, _m, _err);
Reshape(_err, _err, 1, 2 * count);
}
Copy(solver.Param, _param);
for (int i = 0; i < 3; i++)
{
rvec.SetReal1D(i, param[i]);
tvec.SetReal1D(i, param[i + 3]);
}
}
}
