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opencv/modules/calib3d/src/calibration.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/calib3d/calib3d_c.h"
#include <stdio.h>
#include <iterator>
/*
This is stright-forward port v3 of Matlab calibration engine by Jean-Yves Bouguet
that is (in a large extent) based on the paper:
Z. Zhang. "A flexible new technique for camera calibration".
IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334, 2000.
The 1st initial port was done by Valery Mosyagin.
*/
using namespace cv;
// reimplementation of dAB.m
CV_IMPL void cvCalcMatMulDeriv( const CvMat* A, const CvMat* B, CvMat* dABdA, CvMat* dABdB )
{
int i, j, M, N, L;
int bstep;
CV_Assert( CV_IS_MAT(A) && CV_IS_MAT(B) );
CV_Assert( CV_ARE_TYPES_EQ(A, B) &&
(CV_MAT_TYPE(A->type) == CV_32F || CV_MAT_TYPE(A->type) == CV_64F) );
CV_Assert( A->cols == B->rows );
M = A->rows;
L = A->cols;
N = B->cols;
bstep = B->step/CV_ELEM_SIZE(B->type);
if( dABdA )
{
CV_Assert( CV_ARE_TYPES_EQ(A, dABdA) &&
dABdA->rows == A->rows*B->cols && dABdA->cols == A->rows*A->cols );
}
if( dABdB )
{
CV_Assert( CV_ARE_TYPES_EQ(A, dABdB) &&
dABdB->rows == A->rows*B->cols && dABdB->cols == B->rows*B->cols );
}
if( CV_MAT_TYPE(A->type) == CV_32F )
{
for( i = 0; i < M*N; i++ )
{
int i1 = i / N, i2 = i % N;
if( dABdA )
{
float* dcda = (float*)(dABdA->data.ptr + dABdA->step*i);
const float* b = (const float*)B->data.ptr + i2;
for( j = 0; j < M*L; j++ )
dcda[j] = 0;
for( j = 0; j < L; j++ )
dcda[i1*L + j] = b[j*bstep];
}
if( dABdB )
{
float* dcdb = (float*)(dABdB->data.ptr + dABdB->step*i);
const float* a = (const float*)(A->data.ptr + A->step*i1);
for( j = 0; j < L*N; j++ )
dcdb[j] = 0;
for( j = 0; j < L; j++ )
dcdb[j*N + i2] = a[j];
}
}
}
else
{
for( i = 0; i < M*N; i++ )
{
int i1 = i / N, i2 = i % N;
if( dABdA )
{
double* dcda = (double*)(dABdA->data.ptr + dABdA->step*i);
const double* b = (const double*)B->data.ptr + i2;
for( j = 0; j < M*L; j++ )
dcda[j] = 0;
for( j = 0; j < L; j++ )
dcda[i1*L + j] = b[j*bstep];
}
if( dABdB )
{
double* dcdb = (double*)(dABdB->data.ptr + dABdB->step*i);
const double* a = (const double*)(A->data.ptr + A->step*i1);
for( j = 0; j < L*N; j++ )
dcdb[j] = 0;
for( j = 0; j < L; j++ )
dcdb[j*N + i2] = a[j];
}
}
}
}
// reimplementation of compose_motion.m
CV_IMPL void cvComposeRT( const CvMat* _rvec1, const CvMat* _tvec1,
const CvMat* _rvec2, const CvMat* _tvec2,
CvMat* _rvec3, CvMat* _tvec3,
CvMat* dr3dr1, CvMat* dr3dt1,
CvMat* dr3dr2, CvMat* dr3dt2,
CvMat* dt3dr1, CvMat* dt3dt1,
CvMat* dt3dr2, CvMat* dt3dt2 )
{
double _r1[3], _r2[3];
double _R1[9], _d1[9*3], _R2[9], _d2[9*3];
CvMat r1 = cvMat(3,1,CV_64F,_r1), r2 = cvMat(3,1,CV_64F,_r2);
CvMat R1 = cvMat(3,3,CV_64F,_R1), R2 = cvMat(3,3,CV_64F,_R2);
CvMat dR1dr1 = cvMat(9,3,CV_64F,_d1), dR2dr2 = cvMat(9,3,CV_64F,_d2);
CV_Assert( CV_IS_MAT(_rvec1) && CV_IS_MAT(_rvec2) );
CV_Assert( CV_MAT_TYPE(_rvec1->type) == CV_32F ||
CV_MAT_TYPE(_rvec1->type) == CV_64F );
CV_Assert( _rvec1->rows == 3 && _rvec1->cols == 1 && CV_ARE_SIZES_EQ(_rvec1, _rvec2) );
cvConvert( _rvec1, &r1 );
cvConvert( _rvec2, &r2 );
cvRodrigues2( &r1, &R1, &dR1dr1 );
cvRodrigues2( &r2, &R2, &dR2dr2 );
if( _rvec3 || dr3dr1 || dr3dr2 )
{
double _r3[3], _R3[9], _dR3dR1[9*9], _dR3dR2[9*9], _dr3dR3[9*3];
double _W1[9*3], _W2[3*3];
CvMat r3 = cvMat(3,1,CV_64F,_r3), R3 = cvMat(3,3,CV_64F,_R3);
CvMat dR3dR1 = cvMat(9,9,CV_64F,_dR3dR1), dR3dR2 = cvMat(9,9,CV_64F,_dR3dR2);
CvMat dr3dR3 = cvMat(3,9,CV_64F,_dr3dR3);
CvMat W1 = cvMat(3,9,CV_64F,_W1), W2 = cvMat(3,3,CV_64F,_W2);
cvMatMul( &R2, &R1, &R3 );
cvCalcMatMulDeriv( &R2, &R1, &dR3dR2, &dR3dR1 );
cvRodrigues2( &R3, &r3, &dr3dR3 );
if( _rvec3 )
cvConvert( &r3, _rvec3 );
if( dr3dr1 )
{
cvMatMul( &dr3dR3, &dR3dR1, &W1 );
cvMatMul( &W1, &dR1dr1, &W2 );
cvConvert( &W2, dr3dr1 );
}
if( dr3dr2 )
{
cvMatMul( &dr3dR3, &dR3dR2, &W1 );
cvMatMul( &W1, &dR2dr2, &W2 );
cvConvert( &W2, dr3dr2 );
}
}
if( dr3dt1 )
cvZero( dr3dt1 );
if( dr3dt2 )
cvZero( dr3dt2 );
if( _tvec3 || dt3dr2 || dt3dt1 )
{
double _t1[3], _t2[3], _t3[3], _dxdR2[3*9], _dxdt1[3*3], _W3[3*3];
CvMat t1 = cvMat(3,1,CV_64F,_t1), t2 = cvMat(3,1,CV_64F,_t2);
CvMat t3 = cvMat(3,1,CV_64F,_t3);
CvMat dxdR2 = cvMat(3, 9, CV_64F, _dxdR2);
CvMat dxdt1 = cvMat(3, 3, CV_64F, _dxdt1);
CvMat W3 = cvMat(3, 3, CV_64F, _W3);
CV_Assert( CV_IS_MAT(_tvec1) && CV_IS_MAT(_tvec2) );
CV_Assert( CV_ARE_SIZES_EQ(_tvec1, _tvec2) && CV_ARE_SIZES_EQ(_tvec1, _rvec1) );
cvConvert( _tvec1, &t1 );
cvConvert( _tvec2, &t2 );
cvMatMulAdd( &R2, &t1, &t2, &t3 );
if( _tvec3 )
cvConvert( &t3, _tvec3 );
if( dt3dr2 || dt3dt1 )
{
cvCalcMatMulDeriv( &R2, &t1, &dxdR2, &dxdt1 );
if( dt3dr2 )
{
cvMatMul( &dxdR2, &dR2dr2, &W3 );
cvConvert( &W3, dt3dr2 );
}
if( dt3dt1 )
cvConvert( &dxdt1, dt3dt1 );
}
}
if( dt3dt2 )
cvSetIdentity( dt3dt2 );
if( dt3dr1 )
cvZero( dt3dr1 );
}
CV_IMPL int cvRodrigues2( const CvMat* src, CvMat* dst, CvMat* jacobian )
{
int depth, elem_size;
int i, k;
double J[27];
CvMat matJ = cvMat( 3, 9, CV_64F, J );
if( !CV_IS_MAT(src) )
CV_Error( !src ? CV_StsNullPtr : CV_StsBadArg, "Input argument is not a valid matrix" );
if( !CV_IS_MAT(dst) )
CV_Error( !dst ? CV_StsNullPtr : CV_StsBadArg,
"The first output argument is not a valid matrix" );
depth = CV_MAT_DEPTH(src->type);
elem_size = CV_ELEM_SIZE(depth);
if( depth != CV_32F && depth != CV_64F )
CV_Error( CV_StsUnsupportedFormat, "The matrices must have 32f or 64f data type" );
if( !CV_ARE_DEPTHS_EQ(src, dst) )
CV_Error( CV_StsUnmatchedFormats, "All the matrices must have the same data type" );
if( jacobian )
{
if( !CV_IS_MAT(jacobian) )
CV_Error( CV_StsBadArg, "Jacobian is not a valid matrix" );
if( !CV_ARE_DEPTHS_EQ(src, jacobian) || CV_MAT_CN(jacobian->type) != 1 )
CV_Error( CV_StsUnmatchedFormats, "Jacobian must have 32fC1 or 64fC1 datatype" );
if( (jacobian->rows != 9 || jacobian->cols != 3) &&
(jacobian->rows != 3 || jacobian->cols != 9))
CV_Error( CV_StsBadSize, "Jacobian must be 3x9 or 9x3" );
}
if( src->cols == 1 || src->rows == 1 )
{
double rx, ry, rz, theta;
int step = src->rows > 1 ? src->step / elem_size : 1;
if( src->rows + src->cols*CV_MAT_CN(src->type) - 1 != 3 )
CV_Error( CV_StsBadSize, "Input matrix must be 1x3, 3x1 or 3x3" );
if( dst->rows != 3 || dst->cols != 3 || CV_MAT_CN(dst->type) != 1 )
CV_Error( CV_StsBadSize, "Output matrix must be 3x3, single-channel floating point matrix" );
if( depth == CV_32F )
{
rx = src->data.fl[0];
ry = src->data.fl[step];
rz = src->data.fl[step*2];
}
else
{
rx = src->data.db[0];
ry = src->data.db[step];
rz = src->data.db[step*2];
}
theta = std::sqrt(rx*rx + ry*ry + rz*rz);
if( theta < DBL_EPSILON )
{
cvSetIdentity( dst );
if( jacobian )
{
memset( J, 0, sizeof(J) );
J[5] = J[15] = J[19] = -1;
J[7] = J[11] = J[21] = 1;
}
}
else
{
const double I[] = { 1, 0, 0, 0, 1, 0, 0, 0, 1 };
double c = cos(theta);
double s = sin(theta);
double c1 = 1. - c;
double itheta = theta ? 1./theta : 0.;
rx *= itheta; ry *= itheta; rz *= itheta;
double rrt[] = { rx*rx, rx*ry, rx*rz, rx*ry, ry*ry, ry*rz, rx*rz, ry*rz, rz*rz };
double _r_x_[] = { 0, -rz, ry, rz, 0, -rx, -ry, rx, 0 };
double R[9];
CvMat matR = cvMat( 3, 3, CV_64F, R );
// R = cos(theta)*I + (1 - cos(theta))*r*rT + sin(theta)*[r_x]
// where [r_x] is [0 -rz ry; rz 0 -rx; -ry rx 0]
for( k = 0; k < 9; k++ )
R[k] = c*I[k] + c1*rrt[k] + s*_r_x_[k];
cvConvert( &matR, dst );
if( jacobian )
{
double drrt[] = { rx+rx, ry, rz, ry, 0, 0, rz, 0, 0,
0, rx, 0, rx, ry+ry, rz, 0, rz, 0,
0, 0, rx, 0, 0, ry, rx, ry, rz+rz };
double d_r_x_[] = { 0, 0, 0, 0, 0, -1, 0, 1, 0,
0, 0, 1, 0, 0, 0, -1, 0, 0,
0, -1, 0, 1, 0, 0, 0, 0, 0 };
for( i = 0; i < 3; i++ )
{
double ri = i == 0 ? rx : i == 1 ? ry : rz;
double a0 = -s*ri, a1 = (s - 2*c1*itheta)*ri, a2 = c1*itheta;
double a3 = (c - s*itheta)*ri, a4 = s*itheta;
for( k = 0; k < 9; k++ )
J[i*9+k] = a0*I[k] + a1*rrt[k] + a2*drrt[i*9+k] +
a3*_r_x_[k] + a4*d_r_x_[i*9+k];
}
}
}
}
else if( src->cols == 3 && src->rows == 3 )
{
double R[9], U[9], V[9], W[3], rx, ry, rz;
CvMat matR = cvMat( 3, 3, CV_64F, R );
CvMat matU = cvMat( 3, 3, CV_64F, U );
CvMat matV = cvMat( 3, 3, CV_64F, V );
CvMat matW = cvMat( 3, 1, CV_64F, W );
double theta, s, c;
int step = dst->rows > 1 ? dst->step / elem_size : 1;
if( (dst->rows != 1 || dst->cols*CV_MAT_CN(dst->type) != 3) &&
(dst->rows != 3 || dst->cols != 1 || CV_MAT_CN(dst->type) != 1))
CV_Error( CV_StsBadSize, "Output matrix must be 1x3 or 3x1" );
cvConvert( src, &matR );
if( !cvCheckArr( &matR, CV_CHECK_RANGE+CV_CHECK_QUIET, -100, 100 ) )
{
cvZero(dst);
if( jacobian )
cvZero(jacobian);
return 0;
}
cvSVD( &matR, &matW, &matU, &matV, CV_SVD_MODIFY_A + CV_SVD_U_T + CV_SVD_V_T );
cvGEMM( &matU, &matV, 1, 0, 0, &matR, CV_GEMM_A_T );
rx = R[7] - R[5];
ry = R[2] - R[6];
rz = R[3] - R[1];
s = std::sqrt((rx*rx + ry*ry + rz*rz)*0.25);
c = (R[0] + R[4] + R[8] - 1)*0.5;
c = c > 1. ? 1. : c < -1. ? -1. : c;
theta = acos(c);
if( s < 1e-5 )
{
double t;
if( c > 0 )
rx = ry = rz = 0;
else
{
t = (R[0] + 1)*0.5;
rx = std::sqrt(MAX(t,0.));
t = (R[4] + 1)*0.5;
ry = std::sqrt(MAX(t,0.))*(R[1] < 0 ? -1. : 1.);
t = (R[8] + 1)*0.5;
rz = std::sqrt(MAX(t,0.))*(R[2] < 0 ? -1. : 1.);
if( fabs(rx) < fabs(ry) && fabs(rx) < fabs(rz) && (R[5] > 0) != (ry*rz > 0) )
rz = -rz;
theta /= std::sqrt(rx*rx + ry*ry + rz*rz);
rx *= theta;
ry *= theta;
rz *= theta;
}
if( jacobian )
{
memset( J, 0, sizeof(J) );
if( c > 0 )
{
J[5] = J[15] = J[19] = -0.5;
J[7] = J[11] = J[21] = 0.5;
}
}
}
else
{
double vth = 1/(2*s);
if( jacobian )
{
double t, dtheta_dtr = -1./s;
// var1 = [vth;theta]
// var = [om1;var1] = [om1;vth;theta]
double dvth_dtheta = -vth*c/s;
double d1 = 0.5*dvth_dtheta*dtheta_dtr;
double d2 = 0.5*dtheta_dtr;
// dvar1/dR = dvar1/dtheta*dtheta/dR = [dvth/dtheta; 1] * dtheta/dtr * dtr/dR
double dvardR[5*9] =
{
0, 0, 0, 0, 0, 1, 0, -1, 0,
0, 0, -1, 0, 0, 0, 1, 0, 0,
0, 1, 0, -1, 0, 0, 0, 0, 0,
d1, 0, 0, 0, d1, 0, 0, 0, d1,
d2, 0, 0, 0, d2, 0, 0, 0, d2
};
// var2 = [om;theta]
double dvar2dvar[] =
{
vth, 0, 0, rx, 0,
0, vth, 0, ry, 0,
0, 0, vth, rz, 0,
0, 0, 0, 0, 1
};
double domegadvar2[] =
{
theta, 0, 0, rx*vth,
0, theta, 0, ry*vth,
0, 0, theta, rz*vth
};
CvMat _dvardR = cvMat( 5, 9, CV_64FC1, dvardR );
CvMat _dvar2dvar = cvMat( 4, 5, CV_64FC1, dvar2dvar );
CvMat _domegadvar2 = cvMat( 3, 4, CV_64FC1, domegadvar2 );
double t0[3*5];
CvMat _t0 = cvMat( 3, 5, CV_64FC1, t0 );
cvMatMul( &_domegadvar2, &_dvar2dvar, &_t0 );
cvMatMul( &_t0, &_dvardR, &matJ );
// transpose every row of matJ (treat the rows as 3x3 matrices)
CV_SWAP(J[1], J[3], t); CV_SWAP(J[2], J[6], t); CV_SWAP(J[5], J[7], t);
CV_SWAP(J[10], J[12], t); CV_SWAP(J[11], J[15], t); CV_SWAP(J[14], J[16], t);
CV_SWAP(J[19], J[21], t); CV_SWAP(J[20], J[24], t); CV_SWAP(J[23], J[25], t);
}
vth *= theta;
rx *= vth; ry *= vth; rz *= vth;
}
if( depth == CV_32F )
{
dst->data.fl[0] = (float)rx;
dst->data.fl[step] = (float)ry;
dst->data.fl[step*2] = (float)rz;
}
else
{
dst->data.db[0] = rx;
dst->data.db[step] = ry;
dst->data.db[step*2] = rz;
}
}
if( jacobian )
{
if( depth == CV_32F )
{
if( jacobian->rows == matJ.rows )
cvConvert( &matJ, jacobian );
else
{
float Jf[3*9];
CvMat _Jf = cvMat( matJ.rows, matJ.cols, CV_32FC1, Jf );
cvConvert( &matJ, &_Jf );
cvTranspose( &_Jf, jacobian );
}
}
else if( jacobian->rows == matJ.rows )
cvCopy( &matJ, jacobian );
else
cvTranspose( &matJ, jacobian );
}
return 1;
}
static const char* cvDistCoeffErr = "Distortion coefficients must be 1x4, 4x1, 1x5, 5x1, 1x8, 8x1, 1x12 or 12x1 floating-point vector";
CV_IMPL void cvProjectPoints2( const CvMat* objectPoints,
const CvMat* r_vec,
const CvMat* t_vec,
const CvMat* A,
const CvMat* distCoeffs,
CvMat* imagePoints, CvMat* dpdr,
CvMat* dpdt, CvMat* dpdf,
CvMat* dpdc, CvMat* dpdk,
double aspectRatio )
{
Ptr<CvMat> matM, _m;
Ptr<CvMat> _dpdr, _dpdt, _dpdc, _dpdf, _dpdk;
int i, j, count;
int calc_derivatives;
const CvPoint3D64f* M;
CvPoint2D64f* m;
double r[3], R[9], dRdr[27], t[3], a[9], k[12] = {0,0,0,0,0,0,0,0,0,0,0,0}, fx, fy, cx, cy;
CvMat _r, _t, _a = cvMat( 3, 3, CV_64F, a ), _k;
CvMat matR = cvMat( 3, 3, CV_64F, R ), _dRdr = cvMat( 3, 9, CV_64F, dRdr );
double *dpdr_p = 0, *dpdt_p = 0, *dpdk_p = 0, *dpdf_p = 0, *dpdc_p = 0;
int dpdr_step = 0, dpdt_step = 0, dpdk_step = 0, dpdf_step = 0, dpdc_step = 0;
bool fixedAspectRatio = aspectRatio > FLT_EPSILON;
if( !CV_IS_MAT(objectPoints) || !CV_IS_MAT(r_vec) ||
!CV_IS_MAT(t_vec) || !CV_IS_MAT(A) ||
/*!CV_IS_MAT(distCoeffs) ||*/ !CV_IS_MAT(imagePoints) )
CV_Error( CV_StsBadArg, "One of required arguments is not a valid matrix" );
int total = objectPoints->rows * objectPoints->cols * CV_MAT_CN(objectPoints->type);
if(total % 3 != 0)
{
//we have stopped support of homogeneous coordinates because it cause ambiguity in interpretation of the input data
CV_Error( CV_StsBadArg, "Homogeneous coordinates are not supported" );
}
count = total / 3;
if( CV_IS_CONT_MAT(objectPoints->type) &&
(CV_MAT_DEPTH(objectPoints->type) == CV_32F || CV_MAT_DEPTH(objectPoints->type) == CV_64F)&&
((objectPoints->rows == 1 && CV_MAT_CN(objectPoints->type) == 3) ||
(objectPoints->rows == count && CV_MAT_CN(objectPoints->type)*objectPoints->cols == 3) ||
(objectPoints->rows == 3 && CV_MAT_CN(objectPoints->type) == 1 && objectPoints->cols == count)))
{
matM.reset(cvCreateMat( objectPoints->rows, objectPoints->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(objectPoints->type)) ));
cvConvert(objectPoints, matM);
}
else
{
// matM = cvCreateMat( 1, count, CV_64FC3 );
// cvConvertPointsHomogeneous( objectPoints, matM );
CV_Error( CV_StsBadArg, "Homogeneous coordinates are not supported" );
}
if( CV_IS_CONT_MAT(imagePoints->type) &&
(CV_MAT_DEPTH(imagePoints->type) == CV_32F || CV_MAT_DEPTH(imagePoints->type) == CV_64F) &&
((imagePoints->rows == 1 && CV_MAT_CN(imagePoints->type) == 2) ||
(imagePoints->rows == count && CV_MAT_CN(imagePoints->type)*imagePoints->cols == 2) ||
(imagePoints->rows == 2 && CV_MAT_CN(imagePoints->type) == 1 && imagePoints->cols == count)))
{
_m.reset(cvCreateMat( imagePoints->rows, imagePoints->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(imagePoints->type)) ));
cvConvert(imagePoints, _m);
}
else
{
// _m = cvCreateMat( 1, count, CV_64FC2 );
CV_Error( CV_StsBadArg, "Homogeneous coordinates are not supported" );
}
M = (CvPoint3D64f*)matM->data.db;
m = (CvPoint2D64f*)_m->data.db;
if( (CV_MAT_DEPTH(r_vec->type) != CV_64F && CV_MAT_DEPTH(r_vec->type) != CV_32F) ||
(((r_vec->rows != 1 && r_vec->cols != 1) ||
r_vec->rows*r_vec->cols*CV_MAT_CN(r_vec->type) != 3) &&
((r_vec->rows != 3 && r_vec->cols != 3) || CV_MAT_CN(r_vec->type) != 1)))
CV_Error( CV_StsBadArg, "Rotation must be represented by 1x3 or 3x1 "
"floating-point rotation vector, or 3x3 rotation matrix" );
if( r_vec->rows == 3 && r_vec->cols == 3 )
{
_r = cvMat( 3, 1, CV_64FC1, r );
cvRodrigues2( r_vec, &_r );
cvRodrigues2( &_r, &matR, &_dRdr );
cvCopy( r_vec, &matR );
}
else
{
_r = cvMat( r_vec->rows, r_vec->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(r_vec->type)), r );
cvConvert( r_vec, &_r );
cvRodrigues2( &_r, &matR, &_dRdr );
}
if( (CV_MAT_DEPTH(t_vec->type) != CV_64F && CV_MAT_DEPTH(t_vec->type) != CV_32F) ||
(t_vec->rows != 1 && t_vec->cols != 1) ||
t_vec->rows*t_vec->cols*CV_MAT_CN(t_vec->type) != 3 )
CV_Error( CV_StsBadArg,
"Translation vector must be 1x3 or 3x1 floating-point vector" );
_t = cvMat( t_vec->rows, t_vec->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(t_vec->type)), t );
cvConvert( t_vec, &_t );
if( (CV_MAT_TYPE(A->type) != CV_64FC1 && CV_MAT_TYPE(A->type) != CV_32FC1) ||
A->rows != 3 || A->cols != 3 )
CV_Error( CV_StsBadArg, "Instrinsic parameters must be 3x3 floating-point matrix" );
cvConvert( A, &_a );
fx = a[0]; fy = a[4];
cx = a[2]; cy = a[5];
if( fixedAspectRatio )
fx = fy*aspectRatio;
if( distCoeffs )
{
if( !CV_IS_MAT(distCoeffs) ||
(CV_MAT_DEPTH(distCoeffs->type) != CV_64F &&
CV_MAT_DEPTH(distCoeffs->type) != CV_32F) ||
(distCoeffs->rows != 1 && distCoeffs->cols != 1) ||
(distCoeffs->rows*distCoeffs->cols*CV_MAT_CN(distCoeffs->type) != 4 &&
distCoeffs->rows*distCoeffs->cols*CV_MAT_CN(distCoeffs->type) != 5 &&
distCoeffs->rows*distCoeffs->cols*CV_MAT_CN(distCoeffs->type) != 8 &&
distCoeffs->rows*distCoeffs->cols*CV_MAT_CN(distCoeffs->type) != 12) )
CV_Error( CV_StsBadArg, cvDistCoeffErr );
_k = cvMat( distCoeffs->rows, distCoeffs->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(distCoeffs->type)), k );
cvConvert( distCoeffs, &_k );
}
if( dpdr )
{
if( !CV_IS_MAT(dpdr) ||
(CV_MAT_TYPE(dpdr->type) != CV_32FC1 &&
CV_MAT_TYPE(dpdr->type) != CV_64FC1) ||
dpdr->rows != count*2 || dpdr->cols != 3 )
CV_Error( CV_StsBadArg, "dp/drot must be 2Nx3 floating-point matrix" );
if( CV_MAT_TYPE(dpdr->type) == CV_64FC1 )
{
_dpdr.reset(cvCloneMat(dpdr));
}
else
_dpdr.reset(cvCreateMat( 2*count, 3, CV_64FC1 ));
dpdr_p = _dpdr->data.db;
dpdr_step = _dpdr->step/sizeof(dpdr_p[0]);
}
if( dpdt )
{
if( !CV_IS_MAT(dpdt) ||
(CV_MAT_TYPE(dpdt->type) != CV_32FC1 &&
CV_MAT_TYPE(dpdt->type) != CV_64FC1) ||
dpdt->rows != count*2 || dpdt->cols != 3 )
CV_Error( CV_StsBadArg, "dp/dT must be 2Nx3 floating-point matrix" );
if( CV_MAT_TYPE(dpdt->type) == CV_64FC1 )
{
_dpdt.reset(cvCloneMat(dpdt));
}
else
_dpdt.reset(cvCreateMat( 2*count, 3, CV_64FC1 ));
dpdt_p = _dpdt->data.db;
dpdt_step = _dpdt->step/sizeof(dpdt_p[0]);
}
if( dpdf )
{
if( !CV_IS_MAT(dpdf) ||
(CV_MAT_TYPE(dpdf->type) != CV_32FC1 && CV_MAT_TYPE(dpdf->type) != CV_64FC1) ||
dpdf->rows != count*2 || dpdf->cols != 2 )
CV_Error( CV_StsBadArg, "dp/df must be 2Nx2 floating-point matrix" );
if( CV_MAT_TYPE(dpdf->type) == CV_64FC1 )
{
_dpdf.reset(cvCloneMat(dpdf));
}
else
_dpdf.reset(cvCreateMat( 2*count, 2, CV_64FC1 ));
dpdf_p = _dpdf->data.db;
dpdf_step = _dpdf->step/sizeof(dpdf_p[0]);
}
if( dpdc )
{
if( !CV_IS_MAT(dpdc) ||
(CV_MAT_TYPE(dpdc->type) != CV_32FC1 && CV_MAT_TYPE(dpdc->type) != CV_64FC1) ||
dpdc->rows != count*2 || dpdc->cols != 2 )
CV_Error( CV_StsBadArg, "dp/dc must be 2Nx2 floating-point matrix" );
if( CV_MAT_TYPE(dpdc->type) == CV_64FC1 )
{
_dpdc.reset(cvCloneMat(dpdc));
}
else
_dpdc.reset(cvCreateMat( 2*count, 2, CV_64FC1 ));
dpdc_p = _dpdc->data.db;
dpdc_step = _dpdc->step/sizeof(dpdc_p[0]);
}
if( dpdk )
{
if( !CV_IS_MAT(dpdk) ||
(CV_MAT_TYPE(dpdk->type) != CV_32FC1 && CV_MAT_TYPE(dpdk->type) != CV_64FC1) ||
dpdk->rows != count*2 || (dpdk->cols != 12 && dpdk->cols != 8 && dpdk->cols != 5 && dpdk->cols != 4 && dpdk->cols != 2) )
CV_Error( CV_StsBadArg, "dp/df must be 2Nx12, 2Nx8, 2Nx5, 2Nx4 or 2Nx2 floating-point matrix" );
if( !distCoeffs )
CV_Error( CV_StsNullPtr, "distCoeffs is NULL while dpdk is not" );
if( CV_MAT_TYPE(dpdk->type) == CV_64FC1 )
{
_dpdk.reset(cvCloneMat(dpdk));
}
else
_dpdk.reset(cvCreateMat( dpdk->rows, dpdk->cols, CV_64FC1 ));
dpdk_p = _dpdk->data.db;
dpdk_step = _dpdk->step/sizeof(dpdk_p[0]);
}
calc_derivatives = dpdr || dpdt || dpdf || dpdc || dpdk;
for( i = 0; i < count; i++ )
{
double X = M[i].x, Y = M[i].y, Z = M[i].z;
double x = R[0]*X + R[1]*Y + R[2]*Z + t[0];
double y = R[3]*X + R[4]*Y + R[5]*Z + t[1];
double z = R[6]*X + R[7]*Y + R[8]*Z + t[2];
double r2, r4, r6, a1, a2, a3, cdist, icdist2;
double xd, yd;
z = z ? 1./z : 1;
x *= z; y *= z;
r2 = x*x + y*y;
r4 = r2*r2;
r6 = r4*r2;
a1 = 2*x*y;
a2 = r2 + 2*x*x;
a3 = r2 + 2*y*y;
cdist = 1 + k[0]*r2 + k[1]*r4 + k[4]*r6;
icdist2 = 1./(1 + k[5]*r2 + k[6]*r4 + k[7]*r6);
xd = x*cdist*icdist2 + k[2]*a1 + k[3]*a2 + k[8]*r2+k[9]*r4;
yd = y*cdist*icdist2 + k[2]*a3 + k[3]*a1 + k[10]*r2+k[11]*r4;
m[i].x = xd*fx + cx;
m[i].y = yd*fy + cy;
if( calc_derivatives )
{
if( dpdc_p )
{
dpdc_p[0] = 1; dpdc_p[1] = 0;
dpdc_p[dpdc_step] = 0;
dpdc_p[dpdc_step+1] = 1;
dpdc_p += dpdc_step*2;
}
if( dpdf_p )
{
if( fixedAspectRatio )
{
dpdf_p[0] = 0; dpdf_p[1] = xd*aspectRatio;
dpdf_p[dpdf_step] = 0;
dpdf_p[dpdf_step+1] = yd;
}
else
{
dpdf_p[0] = xd; dpdf_p[1] = 0;
dpdf_p[dpdf_step] = 0;
dpdf_p[dpdf_step+1] = yd;
}
dpdf_p += dpdf_step*2;
}
if( dpdk_p )
{
dpdk_p[0] = fx*x*icdist2*r2;
dpdk_p[1] = fx*x*icdist2*r4;
dpdk_p[dpdk_step] = fy*y*icdist2*r2;
dpdk_p[dpdk_step+1] = fy*y*icdist2*r4;
if( _dpdk->cols > 2 )
{
dpdk_p[2] = fx*a1;
dpdk_p[3] = fx*a2;
dpdk_p[dpdk_step+2] = fy*a3;
dpdk_p[dpdk_step+3] = fy*a1;
if( _dpdk->cols > 4 )
{
dpdk_p[4] = fx*x*icdist2*r6;
dpdk_p[dpdk_step+4] = fy*y*icdist2*r6;
if( _dpdk->cols > 5 )
{
dpdk_p[5] = fx*x*cdist*(-icdist2)*icdist2*r2;
dpdk_p[dpdk_step+5] = fy*y*cdist*(-icdist2)*icdist2*r2;
dpdk_p[6] = fx*x*icdist2*cdist*(-icdist2)*icdist2*r4;
dpdk_p[dpdk_step+6] = fy*y*cdist*(-icdist2)*icdist2*r4;
dpdk_p[7] = fx*x*icdist2*cdist*(-icdist2)*icdist2*r6;
dpdk_p[dpdk_step+7] = fy*y*cdist*(-icdist2)*icdist2*r6;
if( _dpdk->cols > 8 )
{
dpdk_p[8] = fx*r2; //s1
dpdk_p[9] = fx*r4; //s2
dpdk_p[10] = 0;//s3
dpdk_p[11] = 0;//s4
dpdk_p[dpdk_step+8] = 0; //s1
dpdk_p[dpdk_step+9] = 0; //s2
dpdk_p[dpdk_step+10] = fy*r2; //s3
dpdk_p[dpdk_step+11] = fy*r4; //s4
}
}
}
}
dpdk_p += dpdk_step*2;
}
if( dpdt_p )
{
double dxdt[] = { z, 0, -x*z }, dydt[] = { 0, z, -y*z };
for( j = 0; j < 3; j++ )
{
double dr2dt = 2*x*dxdt[j] + 2*y*dydt[j];
double dcdist_dt = k[0]*dr2dt + 2*k[1]*r2*dr2dt + 3*k[4]*r4*dr2dt;
double dicdist2_dt = -icdist2*icdist2*(k[5]*dr2dt + 2*k[6]*r2*dr2dt + 3*k[7]*r4*dr2dt);
double da1dt = 2*(x*dydt[j] + y*dxdt[j]);
double dmxdt = fx*(dxdt[j]*cdist*icdist2 + x*dcdist_dt*icdist2 + x*cdist*dicdist2_dt +
k[2]*da1dt + k[3]*(dr2dt + 2*x*dxdt[j]) + k[8]*dr2dt + 2*r2*k[9]*dr2dt);
double dmydt = fy*(dydt[j]*cdist*icdist2 + y*dcdist_dt*icdist2 + y*cdist*dicdist2_dt +
k[2]*(dr2dt + 2*y*dydt[j]) + k[3]*da1dt + k[10]*dr2dt + 2*r2*k[11]*dr2dt);
dpdt_p[j] = dmxdt;
dpdt_p[dpdt_step+j] = dmydt;
}
dpdt_p += dpdt_step*2;
}
if( dpdr_p )
{
double dx0dr[] =
{
X*dRdr[0] + Y*dRdr[1] + Z*dRdr[2],
X*dRdr[9] + Y*dRdr[10] + Z*dRdr[11],
X*dRdr[18] + Y*dRdr[19] + Z*dRdr[20]
};
double dy0dr[] =
{
X*dRdr[3] + Y*dRdr[4] + Z*dRdr[5],
X*dRdr[12] + Y*dRdr[13] + Z*dRdr[14],
X*dRdr[21] + Y*dRdr[22] + Z*dRdr[23]
};
double dz0dr[] =
{
X*dRdr[6] + Y*dRdr[7] + Z*dRdr[8],
X*dRdr[15] + Y*dRdr[16] + Z*dRdr[17],
X*dRdr[24] + Y*dRdr[25] + Z*dRdr[26]
};
for( j = 0; j < 3; j++ )
{
double dxdr = z*(dx0dr[j] - x*dz0dr[j]);
double dydr = z*(dy0dr[j] - y*dz0dr[j]);
double dr2dr = 2*x*dxdr + 2*y*dydr;
double dcdist_dr = k[0]*dr2dr + 2*k[1]*r2*dr2dr + 3*k[4]*r4*dr2dr;
double dicdist2_dr = -icdist2*icdist2*(k[5]*dr2dr + 2*k[6]*r2*dr2dr + 3*k[7]*r4*dr2dr);
double da1dr = 2*(x*dydr + y*dxdr);
double dmxdr = fx*(dxdr*cdist*icdist2 + x*dcdist_dr*icdist2 + x*cdist*dicdist2_dr +
k[2]*da1dr + k[3]*(dr2dr + 2*x*dxdr) + k[8]*dr2dr + 2*r2*k[9]*dr2dr);
double dmydr = fy*(dydr*cdist*icdist2 + y*dcdist_dr*icdist2 + y*cdist*dicdist2_dr +
k[2]*(dr2dr + 2*y*dydr) + k[3]*da1dr + k[10]*dr2dr + 2*r2*k[11]*dr2dr);
dpdr_p[j] = dmxdr;
dpdr_p[dpdr_step+j] = dmydr;
}
dpdr_p += dpdr_step*2;
}
}
}
if( _m != imagePoints )
cvConvert( _m, imagePoints );
if( _dpdr != dpdr )
cvConvert( _dpdr, dpdr );
if( _dpdt != dpdt )
cvConvert( _dpdt, dpdt );
if( _dpdf != dpdf )
cvConvert( _dpdf, dpdf );
if( _dpdc != dpdc )
cvConvert( _dpdc, dpdc );
if( _dpdk != dpdk )
cvConvert( _dpdk, dpdk );
}
CV_IMPL void cvFindExtrinsicCameraParams2( const CvMat* objectPoints,
const CvMat* imagePoints, const CvMat* A,
const CvMat* distCoeffs, CvMat* rvec, CvMat* tvec,
int useExtrinsicGuess )
{
const int max_iter = 20;
Ptr<CvMat> matM, _Mxy, _m, _mn, matL;
int i, count;
double a[9], ar[9]={1,0,0,0,1,0,0,0,1}, R[9];
double MM[9], U[9], V[9], W[3];
CvScalar Mc;
double param[6];
CvMat matA = cvMat( 3, 3, CV_64F, a );
CvMat _Ar = cvMat( 3, 3, CV_64F, ar );
CvMat matR = cvMat( 3, 3, CV_64F, R );
CvMat _r = cvMat( 3, 1, CV_64F, param );
CvMat _t = cvMat( 3, 1, CV_64F, param + 3 );
CvMat _Mc = cvMat( 1, 3, CV_64F, Mc.val );
CvMat _MM = cvMat( 3, 3, CV_64F, MM );
CvMat matU = cvMat( 3, 3, CV_64F, U );
CvMat matV = cvMat( 3, 3, CV_64F, V );
CvMat matW = cvMat( 3, 1, CV_64F, W );
CvMat _param = cvMat( 6, 1, CV_64F, param );
CvMat _dpdr, _dpdt;
CV_Assert( CV_IS_MAT(objectPoints) && CV_IS_MAT(imagePoints) &&
CV_IS_MAT(A) && CV_IS_MAT(rvec) && CV_IS_MAT(tvec) );
count = MAX(objectPoints->cols, objectPoints->rows);
matM.reset(cvCreateMat( 1, count, CV_64FC3 ));
_m.reset(cvCreateMat( 1, count, CV_64FC2 ));
cvConvertPointsHomogeneous( objectPoints, matM );
cvConvertPointsHomogeneous( imagePoints, _m );
cvConvert( A, &matA );
CV_Assert( (CV_MAT_DEPTH(rvec->type) == CV_64F || CV_MAT_DEPTH(rvec->type) == CV_32F) &&
(rvec->rows == 1 || rvec->cols == 1) && rvec->rows*rvec->cols*CV_MAT_CN(rvec->type) == 3 );
CV_Assert( (CV_MAT_DEPTH(tvec->type) == CV_64F || CV_MAT_DEPTH(tvec->type) == CV_32F) &&
(tvec->rows == 1 || tvec->cols == 1) && tvec->rows*tvec->cols*CV_MAT_CN(tvec->type) == 3 );
_mn.reset(cvCreateMat( 1, count, CV_64FC2 ));
_Mxy.reset(cvCreateMat( 1, count, CV_64FC2 ));
// normalize image points
// (unapply the intrinsic matrix transformation and distortion)
cvUndistortPoints( _m, _mn, &matA, distCoeffs, 0, &_Ar );
if( useExtrinsicGuess )
{
CvMat _r_temp = cvMat(rvec->rows, rvec->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(rvec->type)), param );
CvMat _t_temp = cvMat(tvec->rows, tvec->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(tvec->type)), param + 3);
cvConvert( rvec, &_r_temp );
cvConvert( tvec, &_t_temp );
}
else
{
Mc = cvAvg(matM);
cvReshape( matM, matM, 1, count );
cvMulTransposed( matM, &_MM, 1, &_Mc );
cvSVD( &_MM, &matW, 0, &matV, CV_SVD_MODIFY_A + CV_SVD_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 tt[3], h[9], h1_norm, h2_norm;
CvMat* R_transform = &matV;
CvMat T_transform = cvMat( 3, 1, CV_64F, tt );
CvMat matH = cvMat( 3, 3, CV_64F, h );
CvMat _h1, _h2, _h3;
if( V[2]*V[2] + V[5]*V[5] < 1e-10 )
cvSetIdentity( R_transform );
if( cvDet(R_transform) < 0 )
cvScale( R_transform, R_transform, -1 );
cvGEMM( R_transform, &_Mc, -1, 0, 0, &T_transform, CV_GEMM_B_T );
for( i = 0; i < count; i++ )
{
const double* Rp = R_transform->data.db;
const double* Tp = T_transform.data.db;
const double* src = matM->data.db + i*3;
double* dst = _Mxy->data.db + 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];
}
cvFindHomography( _Mxy, _mn, &matH );
if( cvCheckArr(&matH, CV_CHECK_QUIET) )
{
cvGetCol( &matH, &_h1, 0 );
_h2 = _h1; _h2.data.db++;
_h3 = _h2; _h3.data.db++;
h1_norm = std::sqrt(h[0]*h[0] + h[3]*h[3] + h[6]*h[6]);
h2_norm = std::sqrt(h[1]*h[1] + h[4]*h[4] + h[7]*h[7]);
cvScale( &_h1, &_h1, 1./MAX(h1_norm, DBL_EPSILON) );
cvScale( &_h2, &_h2, 1./MAX(h2_norm, DBL_EPSILON) );
cvScale( &_h3, &_t, 2./MAX(h1_norm + h2_norm, DBL_EPSILON));
cvCrossProduct( &_h1, &_h2, &_h3 );
cvRodrigues2( &matH, &_r );
cvRodrigues2( &_r, &matH );
cvMatMulAdd( &matH, &T_transform, &_t, &_t );
cvMatMul( &matH, R_transform, &matR );
}
else
{
cvSetIdentity( &matR );
cvZero( &_t );
}
cvRodrigues2( &matR, &_r );
}
else
{
// non-planar structure. Use DLT method
double* L;
double LL[12*12], LW[12], LV[12*12], sc;
CvMat _LL = cvMat( 12, 12, CV_64F, LL );
CvMat _LW = cvMat( 12, 1, CV_64F, LW );
CvMat _LV = cvMat( 12, 12, CV_64F, LV );
CvMat _RRt, _RR, _tt;
CvPoint3D64f* M = (CvPoint3D64f*)matM->data.db;
CvPoint2D64f* mn = (CvPoint2D64f*)_mn->data.db;
matL.reset(cvCreateMat( 2*count, 12, CV_64F ));
L = matL->data.db;
for( 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.;
L[4] = L[5] = L[6] = L[7] = 0.;
L[12] = L[13] = L[14] = L[15] = 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;
}
cvMulTransposed( matL, &_LL, 1 );
cvSVD( &_LL, &_LW, 0, &_LV, CV_SVD_MODIFY_A + CV_SVD_V_T );
_RRt = cvMat( 3, 4, CV_64F, LV + 11*12 );
cvGetCols( &_RRt, &_RR, 0, 3 );
cvGetCol( &_RRt, &_tt, 3 );
if( cvDet(&_RR) < 0 )
cvScale( &_RRt, &_RRt, -1 );
sc = cvNorm(&_RR);
cvSVD( &_RR, &matW, &matU, &matV, CV_SVD_MODIFY_A + CV_SVD_U_T + CV_SVD_V_T );
cvGEMM( &matU, &matV, 1, 0, 0, &matR, CV_GEMM_A_T );
cvScale( &_tt, &_t, cvNorm(&matR)/sc );
cvRodrigues2( &matR, &_r );
}
}
cvReshape( matM, matM, 3, 1 );
cvReshape( _mn, _mn, 2, 1 );
// refine extrinsic parameters using iterative algorithm
CvLevMarq solver( 6, count*2, cvTermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER,max_iter,FLT_EPSILON), true);
cvCopy( &_param, solver.param );
for(;;)
{
CvMat *matJ = 0, *_err = 0;
const CvMat *__param = 0;
bool proceed = solver.update( __param, matJ, _err );
cvCopy( __param, &_param );
if( !proceed || !_err )
break;
cvReshape( _err, _err, 2, 1 );
if( matJ )
{
cvGetCols( matJ, &_dpdr, 0, 3 );
cvGetCols( matJ, &_dpdt, 3, 6 );
cvProjectPoints2( matM, &_r, &_t, &matA, distCoeffs,
_err, &_dpdr, &_dpdt, 0, 0, 0 );
}
else
{
cvProjectPoints2( matM, &_r, &_t, &matA, distCoeffs,
_err, 0, 0, 0, 0, 0 );
}
cvSub(_err, _m, _err);
cvReshape( _err, _err, 1, 2*count );
}
cvCopy( solver.param, &_param );
_r = cvMat( rvec->rows, rvec->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(rvec->type)), param );
_t = cvMat( tvec->rows, tvec->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(tvec->type)), param + 3 );
cvConvert( &_r, rvec );
cvConvert( &_t, tvec );
}
CV_IMPL void cvInitIntrinsicParams2D( const CvMat* objectPoints,
const CvMat* imagePoints, const CvMat* npoints,
CvSize imageSize, CvMat* cameraMatrix,
double aspectRatio )
{
Ptr<CvMat> matA, _b, _allH;
int i, j, pos, nimages, ni = 0;
double a[9] = { 0, 0, 0, 0, 0, 0, 0, 0, 1 };
double H[9], f[2];
CvMat _a = cvMat( 3, 3, CV_64F, a );
CvMat matH = cvMat( 3, 3, CV_64F, H );
CvMat _f = cvMat( 2, 1, CV_64F, f );
assert( CV_MAT_TYPE(npoints->type) == CV_32SC1 &&
CV_IS_MAT_CONT(npoints->type) );
nimages = npoints->rows + npoints->cols - 1;
if( (CV_MAT_TYPE(objectPoints->type) != CV_32FC3 &&
CV_MAT_TYPE(objectPoints->type) != CV_64FC3) ||
(CV_MAT_TYPE(imagePoints->type) != CV_32FC2 &&
CV_MAT_TYPE(imagePoints->type) != CV_64FC2) )
CV_Error( CV_StsUnsupportedFormat, "Both object points and image points must be 2D" );
if( objectPoints->rows != 1 || imagePoints->rows != 1 )
CV_Error( CV_StsBadSize, "object points and image points must be a single-row matrices" );
matA.reset(cvCreateMat( 2*nimages, 2, CV_64F ));
_b.reset(cvCreateMat( 2*nimages, 1, CV_64F ));
a[2] = (!imageSize.width) ? 0.5 : (imageSize.width - 1)*0.5;
a[5] = (!imageSize.height) ? 0.5 : (imageSize.height - 1)*0.5;
_allH.reset(cvCreateMat( nimages, 9, CV_64F ));
// extract vanishing points in order to obtain initial value for the focal length
for( i = 0, pos = 0; i < nimages; i++, pos += ni )
{
double* Ap = matA->data.db + i*4;
double* bp = _b->data.db + i*2;
ni = npoints->data.i[i];
double h[3], v[3], d1[3], d2[3];
double n[4] = {0,0,0,0};
CvMat _m, matM;
cvGetCols( objectPoints, &matM, pos, pos + ni );
cvGetCols( imagePoints, &_m, pos, pos + ni );
cvFindHomography( &matM, &_m, &matH );
memcpy( _allH->data.db + i*9, H, sizeof(H) );
H[0] -= H[6]*a[2]; H[1] -= H[7]*a[2]; H[2] -= H[8]*a[2];
H[3] -= H[6]*a[5]; H[4] -= H[7]*a[5]; H[5] -= H[8]*a[5];
for( j = 0; j < 3; j++ )
{
double t0 = H[j*3], t1 = H[j*3+1];
h[j] = t0; v[j] = t1;
d1[j] = (t0 + t1)*0.5;
d2[j] = (t0 - t1)*0.5;
n[0] += t0*t0; n[1] += t1*t1;
n[2] += d1[j]*d1[j]; n[3] += d2[j]*d2[j];
}
for( j = 0; j < 4; j++ )
n[j] = 1./std::sqrt(n[j]);
for( j = 0; j < 3; j++ )
{
h[j] *= n[0]; v[j] *= n[1];
d1[j] *= n[2]; d2[j] *= n[3];
}
Ap[0] = h[0]*v[0]; Ap[1] = h[1]*v[1];
Ap[2] = d1[0]*d2[0]; Ap[3] = d1[1]*d2[1];
bp[0] = -h[2]*v[2]; bp[1] = -d1[2]*d2[2];
}
cvSolve( matA, _b, &_f, CV_NORMAL + CV_SVD );
a[0] = std::sqrt(fabs(1./f[0]));
a[4] = std::sqrt(fabs(1./f[1]));
if( aspectRatio != 0 )
{
double tf = (a[0] + a[4])/(aspectRatio + 1.);
a[0] = aspectRatio*tf;
a[4] = tf;
}
cvConvert( &_a, cameraMatrix );
}
/* finds intrinsic and extrinsic camera parameters
from a few views of known calibration pattern */
CV_IMPL double cvCalibrateCamera2( const CvMat* objectPoints,
const CvMat* imagePoints, const CvMat* npoints,
CvSize imageSize, CvMat* cameraMatrix, CvMat* distCoeffs,
CvMat* rvecs, CvMat* tvecs, int flags, CvTermCriteria termCrit )
{
const int NINTRINSIC = 16;
Ptr<CvMat> matM, _m, _Ji, _Je, _err;
CvLevMarq solver;
double reprojErr = 0;
double A[9], k[12] = {0,0,0,0,0,0,0,0,0,0,0,0};
CvMat matA = cvMat(3, 3, CV_64F, A), _k;
int i, nimages, maxPoints = 0, ni = 0, pos, total = 0, nparams, npstep, cn;
double aspectRatio = 0.;
// 0. check the parameters & allocate buffers
if( !CV_IS_MAT(objectPoints) || !CV_IS_MAT(imagePoints) ||
!CV_IS_MAT(npoints) || !CV_IS_MAT(cameraMatrix) || !CV_IS_MAT(distCoeffs) )
CV_Error( CV_StsBadArg, "One of required vector arguments is not a valid matrix" );
if( imageSize.width <= 0 || imageSize.height <= 0 )
CV_Error( CV_StsOutOfRange, "image width and height must be positive" );
if( CV_MAT_TYPE(npoints->type) != CV_32SC1 ||
(npoints->rows != 1 && npoints->cols != 1) )
CV_Error( CV_StsUnsupportedFormat,
"the array of point counters must be 1-dimensional integer vector" );
//when the thin prism model is used the distortion coefficients matrix must have 12 parameters
if((flags & CV_CALIB_THIN_PRISM_MODEL) && (distCoeffs->cols*distCoeffs->rows != 12))
CV_Error( CV_StsBadArg, "Thin prism model must have 12 parameters in the distortion matrix" );
nimages = npoints->rows*npoints->cols;
npstep = npoints->rows == 1 ? 1 : npoints->step/CV_ELEM_SIZE(npoints->type);
if( rvecs )
{
cn = CV_MAT_CN(rvecs->type);
if( !CV_IS_MAT(rvecs) ||
(CV_MAT_DEPTH(rvecs->type) != CV_32F && CV_MAT_DEPTH(rvecs->type) != CV_64F) ||
((rvecs->rows != nimages || (rvecs->cols*cn != 3 && rvecs->cols*cn != 9)) &&
(rvecs->rows != 1 || rvecs->cols != nimages || cn != 3)) )
CV_Error( CV_StsBadArg, "the output array of rotation vectors must be 3-channel "
"1xn or nx1 array or 1-channel nx3 or nx9 array, where n is the number of views" );
}
if( tvecs )
{
cn = CV_MAT_CN(tvecs->type);
if( !CV_IS_MAT(tvecs) ||
(CV_MAT_DEPTH(tvecs->type) != CV_32F && CV_MAT_DEPTH(tvecs->type) != CV_64F) ||
((tvecs->rows != nimages || tvecs->cols*cn != 3) &&
(tvecs->rows != 1 || tvecs->cols != nimages || cn != 3)) )
CV_Error( CV_StsBadArg, "the output array of translation vectors must be 3-channel "
"1xn or nx1 array or 1-channel nx3 array, where n is the number of views" );
}
if( (CV_MAT_TYPE(cameraMatrix->type) != CV_32FC1 &&
CV_MAT_TYPE(cameraMatrix->type) != CV_64FC1) ||
cameraMatrix->rows != 3 || cameraMatrix->cols != 3 )
CV_Error( CV_StsBadArg,
"Intrinsic parameters must be 3x3 floating-point matrix" );
if( (CV_MAT_TYPE(distCoeffs->type) != CV_32FC1 &&
CV_MAT_TYPE(distCoeffs->type) != CV_64FC1) ||
(distCoeffs->cols != 1 && distCoeffs->rows != 1) ||
(distCoeffs->cols*distCoeffs->rows != 4 &&
distCoeffs->cols*distCoeffs->rows != 5 &&
distCoeffs->cols*distCoeffs->rows != 8 &&
distCoeffs->cols*distCoeffs->rows != 12) )
CV_Error( CV_StsBadArg, cvDistCoeffErr );
for( i = 0; i < nimages; i++ )
{
ni = npoints->data.i[i*npstep];
if( ni < 4 )
{
char buf[100];
sprintf( buf, "The number of points in the view #%d is < 4", i );
CV_Error( CV_StsOutOfRange, buf );
}
maxPoints = MAX( maxPoints, ni );
total += ni;
}
matM.reset(cvCreateMat( 1, total, CV_64FC3 ));
_m.reset(cvCreateMat( 1, total, CV_64FC2 ));
cvConvertPointsHomogeneous( objectPoints, matM );
cvConvertPointsHomogeneous( imagePoints, _m );
nparams = NINTRINSIC + nimages*6;
_Ji.reset(cvCreateMat( maxPoints*2, NINTRINSIC, CV_64FC1 ));
_Je.reset(cvCreateMat( maxPoints*2, 6, CV_64FC1 ));
_err.reset(cvCreateMat( maxPoints*2, 1, CV_64FC1 ));
cvZero( _Ji );
_k = cvMat( distCoeffs->rows, distCoeffs->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(distCoeffs->type)), k);
if( distCoeffs->rows*distCoeffs->cols*CV_MAT_CN(distCoeffs->type) < 8 )
{
if( distCoeffs->rows*distCoeffs->cols*CV_MAT_CN(distCoeffs->type) < 5 )
flags |= CV_CALIB_FIX_K3;
flags |= CV_CALIB_FIX_K4 | CV_CALIB_FIX_K5 | CV_CALIB_FIX_K6;
}
const double minValidAspectRatio = 0.01;
const double maxValidAspectRatio = 100.0;
// 1. initialize intrinsic parameters & LM solver
if( flags & CV_CALIB_USE_INTRINSIC_GUESS )
{
cvConvert( cameraMatrix, &matA );
if( A[0] <= 0 || A[4] <= 0 )
CV_Error( CV_StsOutOfRange, "Focal length (fx and fy) must be positive" );
if( A[2] < 0 || A[2] >= imageSize.width ||
A[5] < 0 || A[5] >= imageSize.height )
CV_Error( CV_StsOutOfRange, "Principal point must be within the image" );
if( fabs(A[1]) > 1e-5 )
CV_Error( CV_StsOutOfRange, "Non-zero skew is not supported by the function" );
if( fabs(A[3]) > 1e-5 || fabs(A[6]) > 1e-5 ||
fabs(A[7]) > 1e-5 || fabs(A[8]-1) > 1e-5 )
CV_Error( CV_StsOutOfRange,
"The intrinsic matrix must have [fx 0 cx; 0 fy cy; 0 0 1] shape" );
A[1] = A[3] = A[6] = A[7] = 0.;
A[8] = 1.;
if( flags & CV_CALIB_FIX_ASPECT_RATIO )
{
aspectRatio = A[0]/A[4];
if( aspectRatio < minValidAspectRatio || aspectRatio > maxValidAspectRatio )
CV_Error( CV_StsOutOfRange,
"The specified aspect ratio (= cameraMatrix[0][0] / cameraMatrix[1][1]) is incorrect" );
}
cvConvert( distCoeffs, &_k );
}
else
{
CvScalar mean, sdv;
cvAvgSdv( matM, &mean, &sdv );
if( fabs(mean.val[2]) > 1e-5 || fabs(sdv.val[2]) > 1e-5 )
CV_Error( CV_StsBadArg,
"For non-planar calibration rigs the initial intrinsic matrix must be specified" );
for( i = 0; i < total; i++ )
((CvPoint3D64f*)matM->data.db)[i].z = 0.;
if( flags & CV_CALIB_FIX_ASPECT_RATIO )
{
aspectRatio = cvmGet(cameraMatrix,0,0);
aspectRatio /= cvmGet(cameraMatrix,1,1);
if( aspectRatio < minValidAspectRatio || aspectRatio > maxValidAspectRatio )
CV_Error( CV_StsOutOfRange,
"The specified aspect ratio (= cameraMatrix[0][0] / cameraMatrix[1][1]) is incorrect" );
}
cvInitIntrinsicParams2D( matM, _m, npoints, imageSize, &matA, aspectRatio );
}
solver.init( nparams, 0, termCrit );
{
double* param = solver.param->data.db;
uchar* mask = solver.mask->data.ptr;
param[0] = A[0]; param[1] = A[4]; param[2] = A[2]; param[3] = A[5];
param[4] = k[0]; param[5] = k[1]; param[6] = k[2]; param[7] = k[3];
param[8] = k[4]; param[9] = k[5]; param[10] = k[6]; param[11] = k[7];
param[12] = k[8]; param[13] = k[9]; param[14] = k[10]; param[15] = k[11];
if( flags & CV_CALIB_FIX_FOCAL_LENGTH )
mask[0] = mask[1] = 0;
if( flags & CV_CALIB_FIX_PRINCIPAL_POINT )
mask[2] = mask[3] = 0;
if( flags & CV_CALIB_ZERO_TANGENT_DIST )
{
param[6] = param[7] = 0;
mask[6] = mask[7] = 0;
}
if( !(flags & CV_CALIB_RATIONAL_MODEL) )
flags |= CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5 + CV_CALIB_FIX_K6;
if( !(flags & CV_CALIB_THIN_PRISM_MODEL))
flags |= CALIB_FIX_S1_S2_S3_S4;
if( flags & CV_CALIB_FIX_K1 )
mask[4] = 0;
if( flags & CV_CALIB_FIX_K2 )
mask[5] = 0;
if( flags & CV_CALIB_FIX_K3 )
mask[8] = 0;
if( flags & CV_CALIB_FIX_K4 )
mask[9] = 0;
if( flags & CV_CALIB_FIX_K5 )
mask[10] = 0;
if( flags & CV_CALIB_FIX_K6 )
mask[11] = 0;
if(flags & CALIB_FIX_S1_S2_S3_S4)
{
mask[12] = 0;
mask[13] = 0;
mask[14] = 0;
mask[15] = 0;
}
}
// 2. initialize extrinsic parameters
for( i = 0, pos = 0; i < nimages; i++, pos += ni )
{
CvMat _Mi, _mi, _ri, _ti;
ni = npoints->data.i[i*npstep];
cvGetRows( solver.param, &_ri, NINTRINSIC + i*6, NINTRINSIC + i*6 + 3 );
cvGetRows( solver.param, &_ti, NINTRINSIC + i*6 + 3, NINTRINSIC + i*6 + 6 );
cvGetCols( matM, &_Mi, pos, pos + ni );
cvGetCols( _m, &_mi, pos, pos + ni );
cvFindExtrinsicCameraParams2( &_Mi, &_mi, &matA, &_k, &_ri, &_ti );
}
// 3. run the optimization
for(;;)
{
const CvMat* _param = 0;
CvMat *_JtJ = 0, *_JtErr = 0;
double* _errNorm = 0;
bool proceed = solver.updateAlt( _param, _JtJ, _JtErr, _errNorm );
double *param = solver.param->data.db, *pparam = solver.prevParam->data.db;
if( flags & CV_CALIB_FIX_ASPECT_RATIO )
{
param[0] = param[1]*aspectRatio;
pparam[0] = pparam[1]*aspectRatio;
}
A[0] = param[0]; A[4] = param[1]; A[2] = param[2]; A[5] = param[3];
k[0] = param[4]; k[1] = param[5]; k[2] = param[6]; k[3] = param[7];
k[4] = param[8]; k[5] = param[9]; k[6] = param[10]; k[7] = param[11];
k[8] = param[12];k[9] = param[13];k[10] = param[14];k[11] = param[15];
if( !proceed )
break;
reprojErr = 0;
for( i = 0, pos = 0; i < nimages; i++, pos += ni )
{
CvMat _Mi, _mi, _ri, _ti, _dpdr, _dpdt, _dpdf, _dpdc, _dpdk, _mp, _part;
ni = npoints->data.i[i*npstep];
cvGetRows( solver.param, &_ri, NINTRINSIC + i*6, NINTRINSIC + i*6 + 3 );
cvGetRows( solver.param, &_ti, NINTRINSIC + i*6 + 3, NINTRINSIC + i*6 + 6 );
cvGetCols( matM, &_Mi, pos, pos + ni );
cvGetCols( _m, &_mi, pos, pos + ni );
_Je->rows = _Ji->rows = _err->rows = ni*2;
cvGetCols( _Je, &_dpdr, 0, 3 );
cvGetCols( _Je, &_dpdt, 3, 6 );
cvGetCols( _Ji, &_dpdf, 0, 2 );
cvGetCols( _Ji, &_dpdc, 2, 4 );
cvGetCols( _Ji, &_dpdk, 4, NINTRINSIC );
cvReshape( _err, &_mp, 2, 1 );
if( _JtJ || _JtErr )
{
cvProjectPoints2( &_Mi, &_ri, &_ti, &matA, &_k, &_mp, &_dpdr, &_dpdt,
(flags & CV_CALIB_FIX_FOCAL_LENGTH) ? 0 : &_dpdf,
(flags & CV_CALIB_FIX_PRINCIPAL_POINT) ? 0 : &_dpdc, &_dpdk,
(flags & CV_CALIB_FIX_ASPECT_RATIO) ? aspectRatio : 0);
}
else
cvProjectPoints2( &_Mi, &_ri, &_ti, &matA, &_k, &_mp );
cvSub( &_mp, &_mi, &_mp );
if( _JtJ || _JtErr )
{
cvGetSubRect( _JtJ, &_part, cvRect(0,0,NINTRINSIC,NINTRINSIC) );
cvGEMM( _Ji, _Ji, 1, &_part, 1, &_part, CV_GEMM_A_T );
cvGetSubRect( _JtJ, &_part, cvRect(NINTRINSIC+i*6,NINTRINSIC+i*6,6,6) );
cvGEMM( _Je, _Je, 1, 0, 0, &_part, CV_GEMM_A_T );
cvGetSubRect( _JtJ, &_part, cvRect(NINTRINSIC+i*6,0,6,NINTRINSIC) );
cvGEMM( _Ji, _Je, 1, 0, 0, &_part, CV_GEMM_A_T );
cvGetRows( _JtErr, &_part, 0, NINTRINSIC );
cvGEMM( _Ji, _err, 1, &_part, 1, &_part, CV_GEMM_A_T );
cvGetRows( _JtErr, &_part, NINTRINSIC + i*6, NINTRINSIC + (i+1)*6 );
cvGEMM( _Je, _err, 1, 0, 0, &_part, CV_GEMM_A_T );
}
double errNorm = cvNorm( &_mp, 0, CV_L2 );
reprojErr += errNorm*errNorm;
}
if( _errNorm )
*_errNorm = reprojErr;
}
// 4. store the results
cvConvert( &matA, cameraMatrix );
cvConvert( &_k, distCoeffs );
for( i = 0; i < nimages; i++ )
{
CvMat src, dst;
if( rvecs )
{
src = cvMat( 3, 1, CV_64F, solver.param->data.db + NINTRINSIC + i*6 );
if( rvecs->rows == nimages && rvecs->cols*CV_MAT_CN(rvecs->type) == 9 )
{
dst = cvMat( 3, 3, CV_MAT_DEPTH(rvecs->type),
rvecs->data.ptr + rvecs->step*i );
cvRodrigues2( &src, &matA );
cvConvert( &matA, &dst );
}
else
{
dst = cvMat( 3, 1, CV_MAT_DEPTH(rvecs->type), rvecs->rows == 1 ?
rvecs->data.ptr + i*CV_ELEM_SIZE(rvecs->type) :
rvecs->data.ptr + rvecs->step*i );
cvConvert( &src, &dst );
}
}
if( tvecs )
{
src = cvMat( 3, 1, CV_64F, solver.param->data.db + NINTRINSIC + i*6 + 3 );
dst = cvMat( 3, 1, CV_MAT_DEPTH(tvecs->type), tvecs->rows == 1 ?
tvecs->data.ptr + i*CV_ELEM_SIZE(tvecs->type) :
tvecs->data.ptr + tvecs->step*i );
cvConvert( &src, &dst );
}
}
return std::sqrt(reprojErr/total);
}
void cvCalibrationMatrixValues( const CvMat *calibMatr, CvSize imgSize,
double apertureWidth, double apertureHeight, double *fovx, double *fovy,
double *focalLength, CvPoint2D64f *principalPoint, double *pasp )
{
double alphax, alphay, mx, my;
int imgWidth = imgSize.width, imgHeight = imgSize.height;
/* Validate parameters. */
if(calibMatr == 0)
CV_Error(CV_StsNullPtr, "Some of parameters is a NULL pointer!");
if(!CV_IS_MAT(calibMatr))
CV_Error(CV_StsUnsupportedFormat, "Input parameters must be a matrices!");
if(calibMatr->cols != 3 || calibMatr->rows != 3)
CV_Error(CV_StsUnmatchedSizes, "Size of matrices must be 3x3!");
alphax = cvmGet(calibMatr, 0, 0);
alphay = cvmGet(calibMatr, 1, 1);
assert(imgWidth != 0 && imgHeight != 0 && alphax != 0.0 && alphay != 0.0);
/* Calculate pixel aspect ratio. */
if(pasp)
*pasp = alphay / alphax;
/* Calculate number of pixel per realworld unit. */
if(apertureWidth != 0.0 && apertureHeight != 0.0) {
mx = imgWidth / apertureWidth;
my = imgHeight / apertureHeight;
} else {
mx = 1.0;
my = *pasp;
}
/* Calculate fovx and fovy. */
if(fovx)
*fovx = 2 * atan(imgWidth / (2 * alphax)) * 180.0 / CV_PI;
if(fovy)
*fovy = 2 * atan(imgHeight / (2 * alphay)) * 180.0 / CV_PI;
/* Calculate focal length. */
if(focalLength)
*focalLength = alphax / mx;
/* Calculate principle point. */
if(principalPoint)
*principalPoint = cvPoint2D64f(cvmGet(calibMatr, 0, 2) / mx, cvmGet(calibMatr, 1, 2) / my);
}
//////////////////////////////// Stereo Calibration ///////////////////////////////////
static int dbCmp( const void* _a, const void* _b )
{
double a = *(const double*)_a;
double b = *(const double*)_b;
return (a > b) - (a < b);
}
double cvStereoCalibrate( const CvMat* _objectPoints, const CvMat* _imagePoints1,
const CvMat* _imagePoints2, const CvMat* _npoints,
CvMat* _cameraMatrix1, CvMat* _distCoeffs1,
CvMat* _cameraMatrix2, CvMat* _distCoeffs2,
CvSize imageSize, CvMat* matR, CvMat* matT,
CvMat* matE, CvMat* matF,
int flags,
CvTermCriteria termCrit )
{
const int NINTRINSIC = 16;
Ptr<CvMat> npoints, err, J_LR, Je, Ji, imagePoints[2], objectPoints, RT0;
CvLevMarq solver;
double reprojErr = 0;
double A[2][9], dk[2][12]={{0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0}}, rlr[9];
CvMat K[2], Dist[2], om_LR, T_LR;
CvMat R_LR = cvMat(3, 3, CV_64F, rlr);
int i, k, p, ni = 0, ofs, nimages, pointsTotal, maxPoints = 0;
int nparams;
bool recomputeIntrinsics = false;
double aspectRatio[2] = {0,0};
CV_Assert( CV_IS_MAT(_imagePoints1) && CV_IS_MAT(_imagePoints2) &&
CV_IS_MAT(_objectPoints) && CV_IS_MAT(_npoints) &&
CV_IS_MAT(matR) && CV_IS_MAT(matT) );
CV_Assert( CV_ARE_TYPES_EQ(_imagePoints1, _imagePoints2) &&
CV_ARE_DEPTHS_EQ(_imagePoints1, _objectPoints) );
CV_Assert( (_npoints->cols == 1 || _npoints->rows == 1) &&
CV_MAT_TYPE(_npoints->type) == CV_32SC1 );
nimages = _npoints->cols + _npoints->rows - 1;
npoints.reset(cvCreateMat( _npoints->rows, _npoints->cols, _npoints->type ));
cvCopy( _npoints, npoints );
for( i = 0, pointsTotal = 0; i < nimages; i++ )
{
maxPoints = MAX(maxPoints, npoints->data.i[i]);
pointsTotal += npoints->data.i[i];
}
objectPoints.reset(cvCreateMat( _objectPoints->rows, _objectPoints->cols,
CV_64FC(CV_MAT_CN(_objectPoints->type))));
cvConvert( _objectPoints, objectPoints );
cvReshape( objectPoints, objectPoints, 3, 1 );
for( k = 0; k < 2; k++ )
{
const CvMat* points = k == 0 ? _imagePoints1 : _imagePoints2;
const CvMat* cameraMatrix = k == 0 ? _cameraMatrix1 : _cameraMatrix2;
const CvMat* distCoeffs = k == 0 ? _distCoeffs1 : _distCoeffs2;
int cn = CV_MAT_CN(_imagePoints1->type);
CV_Assert( (CV_MAT_DEPTH(_imagePoints1->type) == CV_32F ||
CV_MAT_DEPTH(_imagePoints1->type) == CV_64F) &&
((_imagePoints1->rows == pointsTotal && _imagePoints1->cols*cn == 2) ||
(_imagePoints1->rows == 1 && _imagePoints1->cols == pointsTotal && cn == 2)) );
K[k] = cvMat(3,3,CV_64F,A[k]);
Dist[k] = cvMat(1,12,CV_64F,dk[k]);
imagePoints[k].reset(cvCreateMat( points->rows, points->cols, CV_64FC(CV_MAT_CN(points->type))));
cvConvert( points, imagePoints[k] );
cvReshape( imagePoints[k], imagePoints[k], 2, 1 );
if( flags & (CV_CALIB_FIX_INTRINSIC|CV_CALIB_USE_INTRINSIC_GUESS|
CV_CALIB_FIX_ASPECT_RATIO|CV_CALIB_FIX_FOCAL_LENGTH) )
cvConvert( cameraMatrix, &K[k] );
if( flags & (CV_CALIB_FIX_INTRINSIC|CV_CALIB_USE_INTRINSIC_GUESS|
CV_CALIB_FIX_K1|CV_CALIB_FIX_K2|CV_CALIB_FIX_K3|CV_CALIB_FIX_K4|CV_CALIB_FIX_K5|CV_CALIB_FIX_K6) )
{
CvMat tdist = cvMat( distCoeffs->rows, distCoeffs->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(distCoeffs->type)), Dist[k].data.db );
cvConvert( distCoeffs, &tdist );
}
if( !(flags & (CV_CALIB_FIX_INTRINSIC|CV_CALIB_USE_INTRINSIC_GUESS)))
{
cvCalibrateCamera2( objectPoints, imagePoints[k],
npoints, imageSize, &K[k], &Dist[k], 0, 0, flags );
}
}
if( flags & CV_CALIB_SAME_FOCAL_LENGTH )
{
static const int avg_idx[] = { 0, 4, 2, 5, -1 };
for( k = 0; avg_idx[k] >= 0; k++ )
A[0][avg_idx[k]] = A[1][avg_idx[k]] = (A[0][avg_idx[k]] + A[1][avg_idx[k]])*0.5;
}
if( flags & CV_CALIB_FIX_ASPECT_RATIO )
{
for( k = 0; k < 2; k++ )
aspectRatio[k] = A[k][0]/A[k][4];
}
recomputeIntrinsics = (flags & CV_CALIB_FIX_INTRINSIC) == 0;
err.reset(cvCreateMat( maxPoints*2, 1, CV_64F ));
Je.reset(cvCreateMat( maxPoints*2, 6, CV_64F ));
J_LR.reset(cvCreateMat( maxPoints*2, 6, CV_64F ));
Ji.reset(cvCreateMat( maxPoints*2, NINTRINSIC, CV_64F ));
cvZero( Ji );
// we optimize for the inter-camera R(3),t(3), then, optionally,
// for intrinisic parameters of each camera ((fx,fy,cx,cy,k1,k2,p1,p2) ~ 8 parameters).
nparams = 6*(nimages+1) + (recomputeIntrinsics ? NINTRINSIC*2 : 0);
// storage for initial [om(R){i}|t{i}] (in order to compute the median for each component)
RT0.reset(cvCreateMat( 6, nimages, CV_64F ));
solver.init( nparams, 0, termCrit );
if( recomputeIntrinsics )
{
uchar* imask = solver.mask->data.ptr + nparams - NINTRINSIC*2;
if( !(flags & CV_CALIB_RATIONAL_MODEL) )
flags |= CV_CALIB_FIX_K4 | CV_CALIB_FIX_K5 | CV_CALIB_FIX_K6;
if( !(flags & CV_CALIB_THIN_PRISM_MODEL) )
flags |= CV_CALIB_FIX_S1_S2_S3_S4;
if( flags & CV_CALIB_FIX_ASPECT_RATIO )
imask[0] = imask[NINTRINSIC] = 0;
if( flags & CV_CALIB_FIX_FOCAL_LENGTH )
imask[0] = imask[1] = imask[NINTRINSIC] = imask[NINTRINSIC+1] = 0;
if( flags & CV_CALIB_FIX_PRINCIPAL_POINT )
imask[2] = imask[3] = imask[NINTRINSIC+2] = imask[NINTRINSIC+3] = 0;
if( flags & CV_CALIB_ZERO_TANGENT_DIST )
imask[6] = imask[7] = imask[NINTRINSIC+6] = imask[NINTRINSIC+7] = 0;
if( flags & CV_CALIB_FIX_K1 )
imask[4] = imask[NINTRINSIC+4] = 0;
if( flags & CV_CALIB_FIX_K2 )
imask[5] = imask[NINTRINSIC+5] = 0;
if( flags & CV_CALIB_FIX_K3 )
imask[8] = imask[NINTRINSIC+8] = 0;
if( flags & CV_CALIB_FIX_K4 )
imask[9] = imask[NINTRINSIC+9] = 0;
if( flags & CV_CALIB_FIX_K5 )
imask[10] = imask[NINTRINSIC+10] = 0;
if( flags & CV_CALIB_FIX_K6 )
imask[11] = imask[NINTRINSIC+11] = 0;
if( flags & CV_CALIB_FIX_S1_S2_S3_S4 )
{
imask[12] = imask[NINTRINSIC+12] = 0;
imask[13] = imask[NINTRINSIC+13] = 0;
imask[14] = imask[NINTRINSIC+14] = 0;
imask[15] = imask[NINTRINSIC+15] = 0;
}
}
/*
Compute initial estimate of pose
For each image, compute:
R(om) is the rotation matrix of om
om(R) is the rotation vector of R
R_ref = R(om_right) * R(om_left)'
T_ref_list = [T_ref_list; T_right - R_ref * T_left]
om_ref_list = {om_ref_list; om(R_ref)]
om = median(om_ref_list)
T = median(T_ref_list)
*/
for( i = ofs = 0; i < nimages; ofs += ni, i++ )
{
ni = npoints->data.i[i];
CvMat objpt_i;
double _om[2][3], r[2][9], t[2][3];
CvMat om[2], R[2], T[2], imgpt_i[2];
objpt_i = cvMat(1, ni, CV_64FC3, objectPoints->data.db + ofs*3);
for( k = 0; k < 2; k++ )
{
imgpt_i[k] = cvMat(1, ni, CV_64FC2, imagePoints[k]->data.db + ofs*2);
om[k] = cvMat(3, 1, CV_64F, _om[k]);
R[k] = cvMat(3, 3, CV_64F, r[k]);
T[k] = cvMat(3, 1, CV_64F, t[k]);
// FIXME: here we ignore activePoints[k] because of
// the limited API of cvFindExtrnisicCameraParams2
cvFindExtrinsicCameraParams2( &objpt_i, &imgpt_i[k], &K[k], &Dist[k], &om[k], &T[k] );
cvRodrigues2( &om[k], &R[k] );
if( k == 0 )
{
// save initial om_left and T_left
solver.param->data.db[(i+1)*6] = _om[0][0];
solver.param->data.db[(i+1)*6 + 1] = _om[0][1];
solver.param->data.db[(i+1)*6 + 2] = _om[0][2];
solver.param->data.db[(i+1)*6 + 3] = t[0][0];
solver.param->data.db[(i+1)*6 + 4] = t[0][1];
solver.param->data.db[(i+1)*6 + 5] = t[0][2];
}
}
cvGEMM( &R[1], &R[0], 1, 0, 0, &R[0], CV_GEMM_B_T );
cvGEMM( &R[0], &T[0], -1, &T[1], 1, &T[1] );
cvRodrigues2( &R[0], &T[0] );
RT0->data.db[i] = t[0][0];
RT0->data.db[i + nimages] = t[0][1];
RT0->data.db[i + nimages*2] = t[0][2];
RT0->data.db[i + nimages*3] = t[1][0];
RT0->data.db[i + nimages*4] = t[1][1];
RT0->data.db[i + nimages*5] = t[1][2];
}
// find the medians and save the first 6 parameters
for( i = 0; i < 6; i++ )
{
qsort( RT0->data.db + i*nimages, nimages, CV_ELEM_SIZE(RT0->type), dbCmp );
solver.param->data.db[i] = nimages % 2 != 0 ? RT0->data.db[i*nimages + nimages/2] :
(RT0->data.db[i*nimages + nimages/2 - 1] + RT0->data.db[i*nimages + nimages/2])*0.5;
}
if( recomputeIntrinsics )
for( k = 0; k < 2; k++ )
{
double* iparam = solver.param->data.db + (nimages+1)*6 + k*NINTRINSIC;
if( flags & CV_CALIB_ZERO_TANGENT_DIST )
dk[k][2] = dk[k][3] = 0;
iparam[0] = A[k][0]; iparam[1] = A[k][4]; iparam[2] = A[k][2]; iparam[3] = A[k][5];
iparam[4] = dk[k][0]; iparam[5] = dk[k][1]; iparam[6] = dk[k][2];
iparam[7] = dk[k][3]; iparam[8] = dk[k][4]; iparam[9] = dk[k][5];
iparam[10] = dk[k][6]; iparam[11] = dk[k][7];
iparam[12] = dk[k][8];
iparam[13] = dk[k][9];
iparam[14] = dk[k][10];
iparam[15] = dk[k][11];
}
om_LR = cvMat(3, 1, CV_64F, solver.param->data.db);
T_LR = cvMat(3, 1, CV_64F, solver.param->data.db + 3);
for(;;)
{
const CvMat* param = 0;
CvMat tmpimagePoints;
CvMat *JtJ = 0, *JtErr = 0;
double *_errNorm = 0;
double _omR[3], _tR[3];
double _dr3dr1[9], _dr3dr2[9], /*_dt3dr1[9],*/ _dt3dr2[9], _dt3dt1[9], _dt3dt2[9];
CvMat dr3dr1 = cvMat(3, 3, CV_64F, _dr3dr1);
CvMat dr3dr2 = cvMat(3, 3, CV_64F, _dr3dr2);
//CvMat dt3dr1 = cvMat(3, 3, CV_64F, _dt3dr1);
CvMat dt3dr2 = cvMat(3, 3, CV_64F, _dt3dr2);
CvMat dt3dt1 = cvMat(3, 3, CV_64F, _dt3dt1);
CvMat dt3dt2 = cvMat(3, 3, CV_64F, _dt3dt2);
CvMat om[2], T[2], imgpt_i[2];
CvMat dpdrot_hdr, dpdt_hdr, dpdf_hdr, dpdc_hdr, dpdk_hdr;
CvMat *dpdrot = &dpdrot_hdr, *dpdt = &dpdt_hdr, *dpdf = 0, *dpdc = 0, *dpdk = 0;
if( !solver.updateAlt( param, JtJ, JtErr, _errNorm ))
break;
reprojErr = 0;
cvRodrigues2( &om_LR, &R_LR );
om[1] = cvMat(3,1,CV_64F,_omR);
T[1] = cvMat(3,1,CV_64F,_tR);
if( recomputeIntrinsics )
{
double* iparam = solver.param->data.db + (nimages+1)*6;
double* ipparam = solver.prevParam->data.db + (nimages+1)*6;
dpdf = &dpdf_hdr;
dpdc = &dpdc_hdr;
dpdk = &dpdk_hdr;
if( flags & CV_CALIB_SAME_FOCAL_LENGTH )
{
iparam[NINTRINSIC] = iparam[0];
iparam[NINTRINSIC+1] = iparam[1];
ipparam[NINTRINSIC] = ipparam[0];
ipparam[NINTRINSIC+1] = ipparam[1];
}
if( flags & CV_CALIB_FIX_ASPECT_RATIO )
{
iparam[0] = iparam[1]*aspectRatio[0];
iparam[NINTRINSIC] = iparam[NINTRINSIC+1]*aspectRatio[1];
ipparam[0] = ipparam[1]*aspectRatio[0];
ipparam[NINTRINSIC] = ipparam[NINTRINSIC+1]*aspectRatio[1];
}
for( k = 0; k < 2; k++ )
{
A[k][0] = iparam[k*NINTRINSIC+0];
A[k][4] = iparam[k*NINTRINSIC+1];
A[k][2] = iparam[k*NINTRINSIC+2];
A[k][5] = iparam[k*NINTRINSIC+3];
dk[k][0] = iparam[k*NINTRINSIC+4];
dk[k][1] = iparam[k*NINTRINSIC+5];
dk[k][2] = iparam[k*NINTRINSIC+6];
dk[k][3] = iparam[k*NINTRINSIC+7];
dk[k][4] = iparam[k*NINTRINSIC+8];
dk[k][5] = iparam[k*NINTRINSIC+9];
dk[k][6] = iparam[k*NINTRINSIC+10];
dk[k][7] = iparam[k*NINTRINSIC+11];
dk[k][8] = iparam[k*NINTRINSIC+12];
dk[k][9] = iparam[k*NINTRINSIC+13];
dk[k][10] = iparam[k*NINTRINSIC+14];
dk[k][11] = iparam[k*NINTRINSIC+15];
}
}
for( i = ofs = 0; i < nimages; ofs += ni, i++ )
{
ni = npoints->data.i[i];
CvMat objpt_i, _part;
om[0] = cvMat(3,1,CV_64F,solver.param->data.db+(i+1)*6);
T[0] = cvMat(3,1,CV_64F,solver.param->data.db+(i+1)*6+3);
if( JtJ || JtErr )
cvComposeRT( &om[0], &T[0], &om_LR, &T_LR, &om[1], &T[1], &dr3dr1, 0,
&dr3dr2, 0, 0, &dt3dt1, &dt3dr2, &dt3dt2 );
else
cvComposeRT( &om[0], &T[0], &om_LR, &T_LR, &om[1], &T[1] );
objpt_i = cvMat(1, ni, CV_64FC3, objectPoints->data.db + ofs*3);
err->rows = Je->rows = J_LR->rows = Ji->rows = ni*2;
cvReshape( err, &tmpimagePoints, 2, 1 );
cvGetCols( Ji, &dpdf_hdr, 0, 2 );
cvGetCols( Ji, &dpdc_hdr, 2, 4 );
cvGetCols( Ji, &dpdk_hdr, 4, NINTRINSIC );
cvGetCols( Je, &dpdrot_hdr, 0, 3 );
cvGetCols( Je, &dpdt_hdr, 3, 6 );
for( k = 0; k < 2; k++ )
{
double l2err;
imgpt_i[k] = cvMat(1, ni, CV_64FC2, imagePoints[k]->data.db + ofs*2);
if( JtJ || JtErr )
cvProjectPoints2( &objpt_i, &om[k], &T[k], &K[k], &Dist[k],
&tmpimagePoints, dpdrot, dpdt, dpdf, dpdc, dpdk,
(flags & CV_CALIB_FIX_ASPECT_RATIO) ? aspectRatio[k] : 0);
else
cvProjectPoints2( &objpt_i, &om[k], &T[k], &K[k], &Dist[k], &tmpimagePoints );
cvSub( &tmpimagePoints, &imgpt_i[k], &tmpimagePoints );
l2err = cvNorm( &tmpimagePoints, 0, CV_L2 );
if( JtJ || JtErr )
{
int iofs = (nimages+1)*6 + k*NINTRINSIC, eofs = (i+1)*6;
assert( JtJ && JtErr );
if( k == 1 )
{
// d(err_{x|y}R) ~ de3
// convert de3/{dr3,dt3} => de3{dr1,dt1} & de3{dr2,dt2}
for( p = 0; p < ni*2; p++ )
{
CvMat de3dr3 = cvMat( 1, 3, CV_64F, Je->data.ptr + Je->step*p );
CvMat de3dt3 = cvMat( 1, 3, CV_64F, de3dr3.data.db + 3 );
CvMat de3dr2 = cvMat( 1, 3, CV_64F, J_LR->data.ptr + J_LR->step*p );
CvMat de3dt2 = cvMat( 1, 3, CV_64F, de3dr2.data.db + 3 );
double _de3dr1[3], _de3dt1[3];
CvMat de3dr1 = cvMat( 1, 3, CV_64F, _de3dr1 );
CvMat de3dt1 = cvMat( 1, 3, CV_64F, _de3dt1 );
cvMatMul( &de3dr3, &dr3dr1, &de3dr1 );
cvMatMul( &de3dt3, &dt3dt1, &de3dt1 );
cvMatMul( &de3dr3, &dr3dr2, &de3dr2 );
cvMatMulAdd( &de3dt3, &dt3dr2, &de3dr2, &de3dr2 );
cvMatMul( &de3dt3, &dt3dt2, &de3dt2 );
cvCopy( &de3dr1, &de3dr3 );
cvCopy( &de3dt1, &de3dt3 );
}
cvGetSubRect( JtJ, &_part, cvRect(0, 0, 6, 6) );
cvGEMM( J_LR, J_LR, 1, &_part, 1, &_part, CV_GEMM_A_T );
cvGetSubRect( JtJ, &_part, cvRect(eofs, 0, 6, 6) );
cvGEMM( J_LR, Je, 1, 0, 0, &_part, CV_GEMM_A_T );
cvGetRows( JtErr, &_part, 0, 6 );
cvGEMM( J_LR, err, 1, &_part, 1, &_part, CV_GEMM_A_T );
}
cvGetSubRect( JtJ, &_part, cvRect(eofs, eofs, 6, 6) );
cvGEMM( Je, Je, 1, &_part, 1, &_part, CV_GEMM_A_T );
cvGetRows( JtErr, &_part, eofs, eofs + 6 );
cvGEMM( Je, err, 1, &_part, 1, &_part, CV_GEMM_A_T );
if( recomputeIntrinsics )
{
cvGetSubRect( JtJ, &_part, cvRect(iofs, iofs, NINTRINSIC, NINTRINSIC) );
cvGEMM( Ji, Ji, 1, &_part, 1, &_part, CV_GEMM_A_T );
cvGetSubRect( JtJ, &_part, cvRect(iofs, eofs, NINTRINSIC, 6) );
cvGEMM( Je, Ji, 1, &_part, 1, &_part, CV_GEMM_A_T );
if( k == 1 )
{
cvGetSubRect( JtJ, &_part, cvRect(iofs, 0, NINTRINSIC, 6) );
cvGEMM( J_LR, Ji, 1, &_part, 1, &_part, CV_GEMM_A_T );
}
cvGetRows( JtErr, &_part, iofs, iofs + NINTRINSIC );
cvGEMM( Ji, err, 1, &_part, 1, &_part, CV_GEMM_A_T );
}
}
reprojErr += l2err*l2err;
}
}
if(_errNorm)
*_errNorm = reprojErr;
}
cvRodrigues2( &om_LR, &R_LR );
if( matR->rows == 1 || matR->cols == 1 )
cvConvert( &om_LR, matR );
else
cvConvert( &R_LR, matR );
cvConvert( &T_LR, matT );
if( recomputeIntrinsics )
{
cvConvert( &K[0], _cameraMatrix1 );
cvConvert( &K[1], _cameraMatrix2 );
for( k = 0; k < 2; k++ )
{
CvMat* distCoeffs = k == 0 ? _distCoeffs1 : _distCoeffs2;
CvMat tdist = cvMat( distCoeffs->rows, distCoeffs->cols,
CV_MAKETYPE(CV_64F,CV_MAT_CN(distCoeffs->type)), Dist[k].data.db );
cvConvert( &tdist, distCoeffs );
}
}
if( matE || matF )
{
double* t = T_LR.data.db;
double tx[] =
{
0, -t[2], t[1],
t[2], 0, -t[0],
-t[1], t[0], 0
};
CvMat Tx = cvMat(3, 3, CV_64F, tx);
double e[9], f[9];
CvMat E = cvMat(3, 3, CV_64F, e);
CvMat F = cvMat(3, 3, CV_64F, f);
cvMatMul( &Tx, &R_LR, &E );
if( matE )
cvConvert( &E, matE );
if( matF )
{
double ik[9];
CvMat iK = cvMat(3, 3, CV_64F, ik);
cvInvert(&K[1], &iK);
cvGEMM( &iK, &E, 1, 0, 0, &E, CV_GEMM_A_T );
cvInvert(&K[0], &iK);
cvMatMul(&E, &iK, &F);
cvConvertScale( &F, matF, fabs(f[8]) > 0 ? 1./f[8] : 1 );
}
}
return std::sqrt(reprojErr/(pointsTotal*2));
}
static void
icvGetRectangles( const CvMat* cameraMatrix, const CvMat* distCoeffs,
const CvMat* R, const CvMat* newCameraMatrix, CvSize imgSize,
cv::Rect_<float>& inner, cv::Rect_<float>& outer )
{
const int N = 9;
int x, y, k;
cv::Ptr<CvMat> _pts(cvCreateMat(1, N*N, CV_32FC2));
CvPoint2D32f* pts = (CvPoint2D32f*)(_pts->data.ptr);
for( y = k = 0; y < N; y++ )
for( x = 0; x < N; x++ )
pts[k++] = cvPoint2D32f((float)x*imgSize.width/(N-1),
(float)y*imgSize.height/(N-1));
cvUndistortPoints(_pts, _pts, cameraMatrix, distCoeffs, R, newCameraMatrix);
float iX0=-FLT_MAX, iX1=FLT_MAX, iY0=-FLT_MAX, iY1=FLT_MAX;
float oX0=FLT_MAX, oX1=-FLT_MAX, oY0=FLT_MAX, oY1=-FLT_MAX;
// find the inscribed rectangle.
// the code will likely not work with extreme rotation matrices (R) (>45%)
for( y = k = 0; y < N; y++ )
for( x = 0; x < N; x++ )
{
CvPoint2D32f p = pts[k++];
oX0 = MIN(oX0, p.x);
oX1 = MAX(oX1, p.x);
oY0 = MIN(oY0, p.y);
oY1 = MAX(oY1, p.y);
if( x == 0 )
iX0 = MAX(iX0, p.x);
if( x == N-1 )
iX1 = MIN(iX1, p.x);
if( y == 0 )
iY0 = MAX(iY0, p.y);
if( y == N-1 )
iY1 = MIN(iY1, p.y);
}
inner = cv::Rect_<float>(iX0, iY0, iX1-iX0, iY1-iY0);
outer = cv::Rect_<float>(oX0, oY0, oX1-oX0, oY1-oY0);
}
void cvStereoRectify( const CvMat* _cameraMatrix1, const CvMat* _cameraMatrix2,
const CvMat* _distCoeffs1, const CvMat* _distCoeffs2,
CvSize imageSize, const CvMat* matR, const CvMat* matT,
CvMat* _R1, CvMat* _R2, CvMat* _P1, CvMat* _P2,
CvMat* matQ, int flags, double alpha, CvSize newImgSize,
CvRect* roi1, CvRect* roi2 )
{
double _om[3], _t[3], _uu[3]={0,0,0}, _r_r[3][3], _pp[3][4];
double _ww[3], _wr[3][3], _z[3] = {0,0,0}, _ri[3][3];
cv::Rect_<float> inner1, inner2, outer1, outer2;
CvMat om = cvMat(3, 1, CV_64F, _om);
CvMat t = cvMat(3, 1, CV_64F, _t);
CvMat uu = cvMat(3, 1, CV_64F, _uu);
CvMat r_r = cvMat(3, 3, CV_64F, _r_r);
CvMat pp = cvMat(3, 4, CV_64F, _pp);
CvMat ww = cvMat(3, 1, CV_64F, _ww); // temps
CvMat wR = cvMat(3, 3, CV_64F, _wr);
CvMat Z = cvMat(3, 1, CV_64F, _z);
CvMat Ri = cvMat(3, 3, CV_64F, _ri);
double nx = imageSize.width, ny = imageSize.height;
int i, k;
if( matR->rows == 3 && matR->cols == 3 )
cvRodrigues2(matR, &om); // get vector rotation
else
cvConvert(matR, &om); // it's already a rotation vector
cvConvertScale(&om, &om, -0.5); // get average rotation
cvRodrigues2(&om, &r_r); // rotate cameras to same orientation by averaging
cvMatMul(&r_r, matT, &t);
int idx = fabs(_t[0]) > fabs(_t[1]) ? 0 : 1;
double c = _t[idx], nt = cvNorm(&t, 0, CV_L2);
_uu[idx] = c > 0 ? 1 : -1;
// calculate global Z rotation
cvCrossProduct(&t,&uu,&ww);
double nw = cvNorm(&ww, 0, CV_L2);
if (nw > 0.0)
cvConvertScale(&ww, &ww, acos(fabs(c)/nt)/nw);
cvRodrigues2(&ww, &wR);
// apply to both views
cvGEMM(&wR, &r_r, 1, 0, 0, &Ri, CV_GEMM_B_T);
cvConvert( &Ri, _R1 );
cvGEMM(&wR, &r_r, 1, 0, 0, &Ri, 0);
cvConvert( &Ri, _R2 );
cvMatMul(&Ri, matT, &t);
// calculate projection/camera matrices
// these contain the relevant rectified image internal params (fx, fy=fx, cx, cy)
double fc_new = DBL_MAX;
CvPoint2D64f cc_new[2] = {{0,0}, {0,0}};
for( k = 0; k < 2; k++ ) {
const CvMat* A = k == 0 ? _cameraMatrix1 : _cameraMatrix2;
const CvMat* Dk = k == 0 ? _distCoeffs1 : _distCoeffs2;
double dk1 = Dk ? cvmGet(Dk, 0, 0) : 0;
double fc = cvmGet(A,idx^1,idx^1);
if( dk1 < 0 ) {
fc *= 1 + dk1*(nx*nx + ny*ny)/(4*fc*fc);
}
fc_new = MIN(fc_new, fc);
}
for( k = 0; k < 2; k++ )
{
const CvMat* A = k == 0 ? _cameraMatrix1 : _cameraMatrix2;
const CvMat* Dk = k == 0 ? _distCoeffs1 : _distCoeffs2;
CvPoint2D32f _pts[4];
CvPoint3D32f _pts_3[4];
CvMat pts = cvMat(1, 4, CV_32FC2, _pts);
CvMat pts_3 = cvMat(1, 4, CV_32FC3, _pts_3);
for( i = 0; i < 4; i++ )
{
int j = (i<2) ? 0 : 1;
_pts[i].x = (float)((i % 2)*(nx-1));
_pts[i].y = (float)(j*(ny-1));
}
cvUndistortPoints( &pts, &pts, A, Dk, 0, 0 );
cvConvertPointsHomogeneous( &pts, &pts_3 );
//Change camera matrix to have cc=[0,0] and fc = fc_new
double _a_tmp[3][3];
CvMat A_tmp = cvMat(3, 3, CV_64F, _a_tmp);
_a_tmp[0][0]=fc_new;
_a_tmp[1][1]=fc_new;
_a_tmp[0][2]=0.0;
_a_tmp[1][2]=0.0;
cvProjectPoints2( &pts_3, k == 0 ? _R1 : _R2, &Z, &A_tmp, 0, &pts );
CvScalar avg = cvAvg(&pts);
cc_new[k].x = (nx-1)/2 - avg.val[0];
cc_new[k].y = (ny-1)/2 - avg.val[1];
}
// vertical focal length must be the same for both images to keep the epipolar constraint
// (for horizontal epipolar lines -- TBD: check for vertical epipolar lines)
// use fy for fx also, for simplicity
// For simplicity, set the principal points for both cameras to be the average
// of the two principal points (either one of or both x- and y- coordinates)
if( flags & CV_CALIB_ZERO_DISPARITY )
{
cc_new[0].x = cc_new[1].x = (cc_new[0].x + cc_new[1].x)*0.5;
cc_new[0].y = cc_new[1].y = (cc_new[0].y + cc_new[1].y)*0.5;
}
else if( idx == 0 ) // horizontal stereo
cc_new[0].y = cc_new[1].y = (cc_new[0].y + cc_new[1].y)*0.5;
else // vertical stereo
cc_new[0].x = cc_new[1].x = (cc_new[0].x + cc_new[1].x)*0.5;
cvZero( &pp );
_pp[0][0] = _pp[1][1] = fc_new;
_pp[0][2] = cc_new[0].x;
_pp[1][2] = cc_new[0].y;
_pp[2][2] = 1;
cvConvert(&pp, _P1);
_pp[0][2] = cc_new[1].x;
_pp[1][2] = cc_new[1].y;
_pp[idx][3] = _t[idx]*fc_new; // baseline * focal length
cvConvert(&pp, _P2);
alpha = MIN(alpha, 1.);
icvGetRectangles( _cameraMatrix1, _distCoeffs1, _R1, _P1, imageSize, inner1, outer1 );
icvGetRectangles( _cameraMatrix2, _distCoeffs2, _R2, _P2, imageSize, inner2, outer2 );
{
newImgSize = newImgSize.width*newImgSize.height != 0 ? newImgSize : imageSize;
double cx1_0 = cc_new[0].x;
double cy1_0 = cc_new[0].y;
double cx2_0 = cc_new[1].x;
double cy2_0 = cc_new[1].y;
double cx1 = newImgSize.width*cx1_0/imageSize.width;
double cy1 = newImgSize.height*cy1_0/imageSize.height;
double cx2 = newImgSize.width*cx2_0/imageSize.width;
double cy2 = newImgSize.height*cy2_0/imageSize.height;
double s = 1.;
if( alpha >= 0 )
{
double s0 = std::max(std::max(std::max((double)cx1/(cx1_0 - inner1.x), (double)cy1/(cy1_0 - inner1.y)),
(double)(newImgSize.width - cx1)/(inner1.x + inner1.width - cx1_0)),
(double)(newImgSize.height - cy1)/(inner1.y + inner1.height - cy1_0));
s0 = std::max(std::max(std::max(std::max((double)cx2/(cx2_0 - inner2.x), (double)cy2/(cy2_0 - inner2.y)),
(double)(newImgSize.width - cx2)/(inner2.x + inner2.width - cx2_0)),
(double)(newImgSize.height - cy2)/(inner2.y + inner2.height - cy2_0)),
s0);
double s1 = std::min(std::min(std::min((double)cx1/(cx1_0 - outer1.x), (double)cy1/(cy1_0 - outer1.y)),
(double)(newImgSize.width - cx1)/(outer1.x + outer1.width - cx1_0)),
(double)(newImgSize.height - cy1)/(outer1.y + outer1.height - cy1_0));
s1 = std::min(std::min(std::min(std::min((double)cx2/(cx2_0 - outer2.x), (double)cy2/(cy2_0 - outer2.y)),
(double)(newImgSize.width - cx2)/(outer2.x + outer2.width - cx2_0)),
(double)(newImgSize.height - cy2)/(outer2.y + outer2.height - cy2_0)),
s1);
s = s0*(1 - alpha) + s1*alpha;
}
fc_new *= s;
cc_new[0] = cvPoint2D64f(cx1, cy1);
cc_new[1] = cvPoint2D64f(cx2, cy2);
cvmSet(_P1, 0, 0, fc_new);
cvmSet(_P1, 1, 1, fc_new);
cvmSet(_P1, 0, 2, cx1);
cvmSet(_P1, 1, 2, cy1);
cvmSet(_P2, 0, 0, fc_new);
cvmSet(_P2, 1, 1, fc_new);
cvmSet(_P2, 0, 2, cx2);
cvmSet(_P2, 1, 2, cy2);
cvmSet(_P2, idx, 3, s*cvmGet(_P2, idx, 3));
if(roi1)
{
*roi1 = cv::Rect(cvCeil((inner1.x - cx1_0)*s + cx1),
cvCeil((inner1.y - cy1_0)*s + cy1),
cvFloor(inner1.width*s), cvFloor(inner1.height*s))
& cv::Rect(0, 0, newImgSize.width, newImgSize.height);
}
if(roi2)
{
*roi2 = cv::Rect(cvCeil((inner2.x - cx2_0)*s + cx2),
cvCeil((inner2.y - cy2_0)*s + cy2),
cvFloor(inner2.width*s), cvFloor(inner2.height*s))
& cv::Rect(0, 0, newImgSize.width, newImgSize.height);
}
}
if( matQ )
{
double q[] =
{
1, 0, 0, -cc_new[0].x,
0, 1, 0, -cc_new[0].y,
0, 0, 0, fc_new,
0, 0, -1./_t[idx],
(idx == 0 ? cc_new[0].x - cc_new[1].x : cc_new[0].y - cc_new[1].y)/_t[idx]
};
CvMat Q = cvMat(4, 4, CV_64F, q);
cvConvert( &Q, matQ );
}
}
void cvGetOptimalNewCameraMatrix( const CvMat* cameraMatrix, const CvMat* distCoeffs,
CvSize imgSize, double alpha,
CvMat* newCameraMatrix, CvSize newImgSize,
CvRect* validPixROI, int centerPrincipalPoint )
{
cv::Rect_<float> inner, outer;
newImgSize = newImgSize.width*newImgSize.height != 0 ? newImgSize : imgSize;
double M[3][3];
CvMat matM = cvMat(3, 3, CV_64F, M);
cvConvert(cameraMatrix, &matM);
if( centerPrincipalPoint )
{
double cx0 = M[0][2];
double cy0 = M[1][2];
double cx = (newImgSize.width-1)*0.5;
double cy = (newImgSize.height-1)*0.5;
icvGetRectangles( cameraMatrix, distCoeffs, 0, cameraMatrix, imgSize, inner, outer );
double s0 = std::max(std::max(std::max((double)cx/(cx0 - inner.x), (double)cy/(cy0 - inner.y)),
(double)cx/(inner.x + inner.width - cx0)),
(double)cy/(inner.y + inner.height - cy0));
double s1 = std::min(std::min(std::min((double)cx/(cx0 - outer.x), (double)cy/(cy0 - outer.y)),
(double)cx/(outer.x + outer.width - cx0)),
(double)cy/(outer.y + outer.height - cy0));
double s = s0*(1 - alpha) + s1*alpha;
M[0][0] *= s;
M[1][1] *= s;
M[0][2] = cx;
M[1][2] = cy;
if( validPixROI )
{
inner = cv::Rect_<float>((float)((inner.x - cx0)*s + cx),
(float)((inner.y - cy0)*s + cy),
(float)(inner.width*s),
(float)(inner.height*s));
cv::Rect r(cvCeil(inner.x), cvCeil(inner.y), cvFloor(inner.width), cvFloor(inner.height));
r &= cv::Rect(0, 0, newImgSize.width, newImgSize.height);
*validPixROI = r;
}
}
else
{
// Get inscribed and circumscribed rectangles in normalized
// (independent of camera matrix) coordinates
icvGetRectangles( cameraMatrix, distCoeffs, 0, 0, imgSize, inner, outer );
// Projection mapping inner rectangle to viewport
double fx0 = (newImgSize.width - 1) / inner.width;
double fy0 = (newImgSize.height - 1) / inner.height;
double cx0 = -fx0 * inner.x;
double cy0 = -fy0 * inner.y;
// Projection mapping outer rectangle to viewport
double fx1 = (newImgSize.width - 1) / outer.width;
double fy1 = (newImgSize.height - 1) / outer.height;
double cx1 = -fx1 * outer.x;
double cy1 = -fy1 * outer.y;
// Interpolate between the two optimal projections
M[0][0] = fx0*(1 - alpha) + fx1*alpha;
M[1][1] = fy0*(1 - alpha) + fy1*alpha;
M[0][2] = cx0*(1 - alpha) + cx1*alpha;
M[1][2] = cy0*(1 - alpha) + cy1*alpha;
if( validPixROI )
{
icvGetRectangles( cameraMatrix, distCoeffs, 0, &matM, imgSize, inner, outer );
cv::Rect r = inner;
r &= cv::Rect(0, 0, newImgSize.width, newImgSize.height);
*validPixROI = r;
}
}
cvConvert(&matM, newCameraMatrix);
}
CV_IMPL int cvStereoRectifyUncalibrated(
const CvMat* _points1, const CvMat* _points2,
const CvMat* F0, CvSize imgSize,
CvMat* _H1, CvMat* _H2, double threshold )
{
Ptr<CvMat> _m1, _m2, _lines1, _lines2;
int i, j, npoints;
double cx, cy;
double u[9], v[9], w[9], f[9], h1[9], h2[9], h0[9], e2[3];
CvMat E2 = cvMat( 3, 1, CV_64F, e2 );
CvMat U = cvMat( 3, 3, CV_64F, u );
CvMat V = cvMat( 3, 3, CV_64F, v );
CvMat W = cvMat( 3, 3, CV_64F, w );
CvMat F = cvMat( 3, 3, CV_64F, f );
CvMat H1 = cvMat( 3, 3, CV_64F, h1 );
CvMat H2 = cvMat( 3, 3, CV_64F, h2 );
CvMat H0 = cvMat( 3, 3, CV_64F, h0 );
CvPoint2D64f* m1;
CvPoint2D64f* m2;
CvPoint3D64f* lines1;
CvPoint3D64f* lines2;
CV_Assert( CV_IS_MAT(_points1) && CV_IS_MAT(_points2) &&
(_points1->rows == 1 || _points1->cols == 1) &&
(_points2->rows == 1 || _points2->cols == 1) &&
CV_ARE_SIZES_EQ(_points1, _points2) );
npoints = _points1->rows * _points1->cols * CV_MAT_CN(_points1->type) / 2;
_m1.reset(cvCreateMat( _points1->rows, _points1->cols, CV_64FC(CV_MAT_CN(_points1->type)) ));
_m2.reset(cvCreateMat( _points2->rows, _points2->cols, CV_64FC(CV_MAT_CN(_points2->type)) ));
_lines1.reset(cvCreateMat( 1, npoints, CV_64FC3 ));
_lines2.reset(cvCreateMat( 1, npoints, CV_64FC3 ));
cvConvert( F0, &F );
cvSVD( (CvMat*)&F, &W, &U, &V, CV_SVD_U_T + CV_SVD_V_T );
W.data.db[8] = 0.;
cvGEMM( &U, &W, 1, 0, 0, &W, CV_GEMM_A_T );
cvMatMul( &W, &V, &F );
cx = cvRound( (imgSize.width-1)*0.5 );
cy = cvRound( (imgSize.height-1)*0.5 );
cvZero( _H1 );
cvZero( _H2 );
cvConvert( _points1, _m1 );
cvConvert( _points2, _m2 );
cvReshape( _m1, _m1, 2, 1 );
cvReshape( _m2, _m2, 2, 1 );
m1 = (CvPoint2D64f*)_m1->data.ptr;
m2 = (CvPoint2D64f*)_m2->data.ptr;
lines1 = (CvPoint3D64f*)_lines1->data.ptr;
lines2 = (CvPoint3D64f*)_lines2->data.ptr;
if( threshold > 0 )
{
cvComputeCorrespondEpilines( _m1, 1, &F, _lines1 );
cvComputeCorrespondEpilines( _m2, 2, &F, _lines2 );
// measure distance from points to the corresponding epilines, mark outliers
for( i = j = 0; i < npoints; i++ )
{
if( fabs(m1[i].x*lines2[i].x +
m1[i].y*lines2[i].y +
lines2[i].z) <= threshold &&
fabs(m2[i].x*lines1[i].x +
m2[i].y*lines1[i].y +
lines1[i].z) <= threshold )
{
if( j < i )
{
m1[j] = m1[i];
m2[j] = m2[i];
}
j++;
}
}
npoints = j;
if( npoints == 0 )
return 0;
}
_m1->cols = _m2->cols = npoints;
memcpy( E2.data.db, U.data.db + 6, sizeof(e2));
cvScale( &E2, &E2, e2[2] > 0 ? 1 : -1 );
double t[] =
{
1, 0, -cx,
0, 1, -cy,
0, 0, 1
};
CvMat T = cvMat(3, 3, CV_64F, t);
cvMatMul( &T, &E2, &E2 );
int mirror = e2[0] < 0;
double d = MAX(std::sqrt(e2[0]*e2[0] + e2[1]*e2[1]),DBL_EPSILON);
double alpha = e2[0]/d;
double beta = e2[1]/d;
double r[] =
{
alpha, beta, 0,
-beta, alpha, 0,
0, 0, 1
};
CvMat R = cvMat(3, 3, CV_64F, r);
cvMatMul( &R, &T, &T );
cvMatMul( &R, &E2, &E2 );
double invf = fabs(e2[2]) < 1e-6*fabs(e2[0]) ? 0 : -e2[2]/e2[0];
double k[] =
{
1, 0, 0,
0, 1, 0,
invf, 0, 1
};
CvMat K = cvMat(3, 3, CV_64F, k);
cvMatMul( &K, &T, &H2 );
cvMatMul( &K, &E2, &E2 );
double it[] =
{
1, 0, cx,
0, 1, cy,
0, 0, 1
};
CvMat iT = cvMat( 3, 3, CV_64F, it );
cvMatMul( &iT, &H2, &H2 );
memcpy( E2.data.db, U.data.db + 6, sizeof(e2));
cvScale( &E2, &E2, e2[2] > 0 ? 1 : -1 );
double e2_x[] =
{
0, -e2[2], e2[1],
e2[2], 0, -e2[0],
-e2[1], e2[0], 0
};
double e2_111[] =
{
e2[0], e2[0], e2[0],
e2[1], e2[1], e2[1],
e2[2], e2[2], e2[2],
};
CvMat E2_x = cvMat(3, 3, CV_64F, e2_x);
CvMat E2_111 = cvMat(3, 3, CV_64F, e2_111);
cvMatMulAdd(&E2_x, &F, &E2_111, &H0 );
cvMatMul(&H2, &H0, &H0);
CvMat E1=cvMat(3, 1, CV_64F, V.data.db+6);
cvMatMul(&H0, &E1, &E1);
cvPerspectiveTransform( _m1, _m1, &H0 );
cvPerspectiveTransform( _m2, _m2, &H2 );
CvMat A = cvMat( 1, npoints, CV_64FC3, lines1 ), BxBy, B;
double x[3];
CvMat X = cvMat( 3, 1, CV_64F, x );
cvConvertPointsHomogeneous( _m1, &A );
cvReshape( &A, &A, 1, npoints );
cvReshape( _m2, &BxBy, 1, npoints );
cvGetCol( &BxBy, &B, 0 );
cvSolve( &A, &B, &X, CV_SVD );
double ha[] =
{
x[0], x[1], x[2],
0, 1, 0,
0, 0, 1
};
CvMat Ha = cvMat(3, 3, CV_64F, ha);
cvMatMul( &Ha, &H0, &H1 );
cvPerspectiveTransform( _m1, _m1, &Ha );
if( mirror )
{
double mm[] = { -1, 0, cx*2, 0, -1, cy*2, 0, 0, 1 };
CvMat MM = cvMat(3, 3, CV_64F, mm);
cvMatMul( &MM, &H1, &H1 );
cvMatMul( &MM, &H2, &H2 );
}
cvConvert( &H1, _H1 );
cvConvert( &H2, _H2 );
return 1;
}
void cv::reprojectImageTo3D( InputArray _disparity,
OutputArray __3dImage, InputArray _Qmat,
bool handleMissingValues, int dtype )
{
Mat disparity = _disparity.getMat(), Q = _Qmat.getMat();
int stype = disparity.type();
CV_Assert( stype == CV_8UC1 || stype == CV_16SC1 ||
stype == CV_32SC1 || stype == CV_32FC1 );
CV_Assert( Q.size() == Size(4,4) );
if( dtype < 0 )
dtype = CV_32FC3;
else
{
dtype = CV_MAKETYPE(CV_MAT_DEPTH(dtype), 3);
CV_Assert( dtype == CV_16SC3 || dtype == CV_32SC3 || dtype == CV_32FC3 );
}
__3dImage.create(disparity.size(), CV_MAKETYPE(dtype, 3));
Mat _3dImage = __3dImage.getMat();
const double bigZ = 10000.;
double q[4][4];
Mat _Q(4, 4, CV_64F, q);
Q.convertTo(_Q, CV_64F);
int x, cols = disparity.cols;
CV_Assert( cols >= 0 );
std::vector<float> _sbuf(cols+1), _dbuf(cols*3+1);
float* sbuf = &_sbuf[0], *dbuf = &_dbuf[0];
double minDisparity = FLT_MAX;
// NOTE: here we quietly assume that at least one pixel in the disparity map is not defined.
// and we set the corresponding Z's to some fixed big value.
if( handleMissingValues )
cv::minMaxIdx( disparity, &minDisparity, 0, 0, 0 );
for( int y = 0; y < disparity.rows; y++ )
{
float *sptr = sbuf, *dptr = dbuf;
double qx = q[0][1]*y + q[0][3], qy = q[1][1]*y + q[1][3];
double qz = q[2][1]*y + q[2][3], qw = q[3][1]*y + q[3][3];
if( stype == CV_8UC1 )
{
const uchar* sptr0 = disparity.ptr<uchar>(y);
for( x = 0; x < cols; x++ )
sptr[x] = (float)sptr0[x];
}
else if( stype == CV_16SC1 )
{
const short* sptr0 = disparity.ptr<short>(y);
for( x = 0; x < cols; x++ )
sptr[x] = (float)sptr0[x];
}
else if( stype == CV_32SC1 )
{
const int* sptr0 = disparity.ptr<int>(y);
for( x = 0; x < cols; x++ )
sptr[x] = (float)sptr0[x];
}
else
sptr = (float*)disparity.ptr<float>(y);
if( dtype == CV_32FC3 )
dptr = _3dImage.ptr<float>(y);
for( x = 0; x < cols; x++, qx += q[0][0], qy += q[1][0], qz += q[2][0], qw += q[3][0] )
{
double d = sptr[x];
double iW = 1./(qw + q[3][2]*d);
double X = (qx + q[0][2]*d)*iW;
double Y = (qy + q[1][2]*d)*iW;
double Z = (qz + q[2][2]*d)*iW;
if( fabs(d-minDisparity) <= FLT_EPSILON )
Z = bigZ;
dptr[x*3] = (float)X;
dptr[x*3+1] = (float)Y;
dptr[x*3+2] = (float)Z;
}
if( dtype == CV_16SC3 )
{
short* dptr0 = _3dImage.ptr<short>(y);
for( x = 0; x < cols*3; x++ )
{
int ival = cvRound(dptr[x]);
dptr0[x] = cv::saturate_cast<short>(ival);
}
}
else if( dtype == CV_32SC3 )
{
int* dptr0 = _3dImage.ptr<int>(y);
for( x = 0; x < cols*3; x++ )
{
int ival = cvRound(dptr[x]);
dptr0[x] = ival;
}
}
}
}
void cvReprojectImageTo3D( const CvArr* disparityImage,
CvArr* _3dImage, const CvMat* matQ,
int handleMissingValues )
{
cv::Mat disp = cv::cvarrToMat(disparityImage);
cv::Mat _3dimg = cv::cvarrToMat(_3dImage);
cv::Mat mq = cv::cvarrToMat(matQ);
CV_Assert( disp.size() == _3dimg.size() );
int dtype = _3dimg.type();
CV_Assert( dtype == CV_16SC3 || dtype == CV_32SC3 || dtype == CV_32FC3 );
cv::reprojectImageTo3D(disp, _3dimg, mq, handleMissingValues != 0, dtype );
}
CV_IMPL void
cvRQDecomp3x3( const CvMat *matrixM, CvMat *matrixR, CvMat *matrixQ,
CvMat *matrixQx, CvMat *matrixQy, CvMat *matrixQz,
CvPoint3D64f *eulerAngles)
{
double matM[3][3], matR[3][3], matQ[3][3];
CvMat M = cvMat(3, 3, CV_64F, matM);
CvMat R = cvMat(3, 3, CV_64F, matR);
CvMat Q = cvMat(3, 3, CV_64F, matQ);
double z, c, s;
/* Validate parameters. */
CV_Assert( CV_IS_MAT(matrixM) && CV_IS_MAT(matrixR) && CV_IS_MAT(matrixQ) &&
matrixM->cols == 3 && matrixM->rows == 3 &&
CV_ARE_SIZES_EQ(matrixM, matrixR) && CV_ARE_SIZES_EQ(matrixM, matrixQ));
cvConvert(matrixM, &M);
/* Find Givens rotation Q_x for x axis (left multiplication). */
/*
( 1 0 0 )
Qx = ( 0 c s ), c = m33/sqrt(m32^2 + m33^2), s = m32/sqrt(m32^2 + m33^2)
( 0 -s c )
*/
s = matM[2][1];
c = matM[2][2];
z = 1./std::sqrt(c * c + s * s + DBL_EPSILON);
c *= z;
s *= z;
double _Qx[3][3] = { {1, 0, 0}, {0, c, s}, {0, -s, c} };
CvMat Qx = cvMat(3, 3, CV_64F, _Qx);
cvMatMul(&M, &Qx, &R);
assert(fabs(matR[2][1]) < FLT_EPSILON);
matR[2][1] = 0;
/* Find Givens rotation for y axis. */
/*
( c 0 -s )
Qy = ( 0 1 0 ), c = m33/sqrt(m31^2 + m33^2), s = -m31/sqrt(m31^2 + m33^2)
( s 0 c )
*/
s = -matR[2][0];
c = matR[2][2];
z = 1./std::sqrt(c * c + s * s + DBL_EPSILON);
c *= z;
s *= z;
double _Qy[3][3] = { {c, 0, -s}, {0, 1, 0}, {s, 0, c} };
CvMat Qy = cvMat(3, 3, CV_64F, _Qy);
cvMatMul(&R, &Qy, &M);
assert(fabs(matM[2][0]) < FLT_EPSILON);
matM[2][0] = 0;
/* Find Givens rotation for z axis. */
/*
( c s 0 )
Qz = (-s c 0 ), c = m22/sqrt(m21^2 + m22^2), s = m21/sqrt(m21^2 + m22^2)
( 0 0 1 )
*/
s = matM[1][0];
c = matM[1][1];
z = 1./std::sqrt(c * c + s * s + DBL_EPSILON);
c *= z;
s *= z;
double _Qz[3][3] = { {c, s, 0}, {-s, c, 0}, {0, 0, 1} };
CvMat Qz = cvMat(3, 3, CV_64F, _Qz);
cvMatMul(&M, &Qz, &R);
assert(fabs(matR[1][0]) < FLT_EPSILON);
matR[1][0] = 0;
// Solve the decomposition ambiguity.
// Diagonal entries of R, except the last one, shall be positive.
// Further rotate R by 180 degree if necessary
if( matR[0][0] < 0 )
{
if( matR[1][1] < 0 )
{
// rotate around z for 180 degree, i.e. a rotation matrix of
// [-1, 0, 0],
// [ 0, -1, 0],
// [ 0, 0, 1]
matR[0][0] *= -1;
matR[0][1] *= -1;
matR[1][1] *= -1;
_Qz[0][0] *= -1;
_Qz[0][1] *= -1;
_Qz[1][0] *= -1;
_Qz[1][1] *= -1;
}
else
{
// rotate around y for 180 degree, i.e. a rotation matrix of
// [-1, 0, 0],
// [ 0, 1, 0],
// [ 0, 0, -1]
matR[0][0] *= -1;
matR[0][2] *= -1;
matR[1][2] *= -1;
matR[2][2] *= -1;
cvTranspose( &Qz, &Qz );
_Qy[0][0] *= -1;
_Qy[0][2] *= -1;
_Qy[2][0] *= -1;
_Qy[2][2] *= -1;
}
}
else if( matR[1][1] < 0 )
{
// ??? for some reason, we never get here ???
// rotate around x for 180 degree, i.e. a rotation matrix of
// [ 1, 0, 0],
// [ 0, -1, 0],
// [ 0, 0, -1]
matR[0][1] *= -1;
matR[0][2] *= -1;
matR[1][1] *= -1;
matR[1][2] *= -1;
matR[2][2] *= -1;
cvTranspose( &Qz, &Qz );
cvTranspose( &Qy, &Qy );
_Qx[1][1] *= -1;
_Qx[1][2] *= -1;
_Qx[2][1] *= -1;
_Qx[2][2] *= -1;
}
// calculate the euler angle
if( eulerAngles )
{
eulerAngles->x = acos(_Qx[1][1]) * (_Qx[1][2] >= 0 ? 1 : -1) * (180.0 / CV_PI);
eulerAngles->y = acos(_Qy[0][0]) * (_Qy[2][0] >= 0 ? 1 : -1) * (180.0 / CV_PI);
eulerAngles->z = acos(_Qz[0][0]) * (_Qz[0][1] >= 0 ? 1 : -1) * (180.0 / CV_PI);
}
/* Calulate orthogonal matrix. */
/*
Q = QzT * QyT * QxT
*/
cvGEMM( &Qz, &Qy, 1, 0, 0, &M, CV_GEMM_A_T + CV_GEMM_B_T );
cvGEMM( &M, &Qx, 1, 0, 0, &Q, CV_GEMM_B_T );
/* Save R and Q matrices. */
cvConvert( &R, matrixR );
cvConvert( &Q, matrixQ );
if( matrixQx )
cvConvert(&Qx, matrixQx);
if( matrixQy )
cvConvert(&Qy, matrixQy);
if( matrixQz )
cvConvert(&Qz, matrixQz);
}
CV_IMPL void
cvDecomposeProjectionMatrix( const CvMat *projMatr, CvMat *calibMatr,
CvMat *rotMatr, CvMat *posVect,
CvMat *rotMatrX, CvMat *rotMatrY,
CvMat *rotMatrZ, CvPoint3D64f *eulerAngles)
{
double tmpProjMatrData[16], tmpMatrixDData[16], tmpMatrixVData[16];
CvMat tmpProjMatr = cvMat(4, 4, CV_64F, tmpProjMatrData);
CvMat tmpMatrixD = cvMat(4, 4, CV_64F, tmpMatrixDData);
CvMat tmpMatrixV = cvMat(4, 4, CV_64F, tmpMatrixVData);
CvMat tmpMatrixM;
/* Validate parameters. */
if(projMatr == 0 || calibMatr == 0 || rotMatr == 0 || posVect == 0)
CV_Error(CV_StsNullPtr, "Some of parameters is a NULL pointer!");
if(!CV_IS_MAT(projMatr) || !CV_IS_MAT(calibMatr) || !CV_IS_MAT(rotMatr) || !CV_IS_MAT(posVect))
CV_Error(CV_StsUnsupportedFormat, "Input parameters must be a matrices!");
if(projMatr->cols != 4 || projMatr->rows != 3)
CV_Error(CV_StsUnmatchedSizes, "Size of projection matrix must be 3x4!");
if(calibMatr->cols != 3 || calibMatr->rows != 3 || rotMatr->cols != 3 || rotMatr->rows != 3)
CV_Error(CV_StsUnmatchedSizes, "Size of calibration and rotation matrices must be 3x3!");
if(posVect->cols != 1 || posVect->rows != 4)
CV_Error(CV_StsUnmatchedSizes, "Size of position vector must be 4x1!");
/* Compute position vector. */
cvSetZero(&tmpProjMatr); // Add zero row to make matrix square.
int i, k;
for(i = 0; i < 3; i++)
for(k = 0; k < 4; k++)
cvmSet(&tmpProjMatr, i, k, cvmGet(projMatr, i, k));
cvSVD(&tmpProjMatr, &tmpMatrixD, NULL, &tmpMatrixV, CV_SVD_MODIFY_A + CV_SVD_V_T);
/* Save position vector. */
for(i = 0; i < 4; i++)
cvmSet(posVect, i, 0, cvmGet(&tmpMatrixV, 3, i)); // Solution is last row of V.
/* Compute calibration and rotation matrices via RQ decomposition. */
cvGetCols(projMatr, &tmpMatrixM, 0, 3); // M is first square matrix of P.
CV_Assert(cvDet(&tmpMatrixM) != 0.0); // So far only finite cameras could be decomposed, so M has to be nonsingular [det(M) != 0].
cvRQDecomp3x3(&tmpMatrixM, calibMatr, rotMatr, rotMatrX, rotMatrY, rotMatrZ, eulerAngles);
}
namespace cv
{
static void collectCalibrationData( InputArrayOfArrays objectPoints,
InputArrayOfArrays imagePoints1,
InputArrayOfArrays imagePoints2,
Mat& objPtMat, Mat& imgPtMat1, Mat* imgPtMat2,
Mat& npoints )
{
int nimages = (int)objectPoints.total();
int i, j = 0, ni = 0, total = 0;
CV_Assert(nimages > 0 && nimages == (int)imagePoints1.total() &&
(!imgPtMat2 || nimages == (int)imagePoints2.total()));
for( i = 0; i < nimages; i++ )
{
ni = objectPoints.getMat(i).checkVector(3, CV_32F);
CV_Assert( ni >= 0 );
total += ni;
}
npoints.create(1, (int)nimages, CV_32S);
objPtMat.create(1, (int)total, CV_32FC3);
imgPtMat1.create(1, (int)total, CV_32FC2);
Point2f* imgPtData2 = 0;
if( imgPtMat2 )
{
imgPtMat2->create(1, (int)total, CV_32FC2);
imgPtData2 = imgPtMat2->ptr<Point2f>();
}
Point3f* objPtData = objPtMat.ptr<Point3f>();
Point2f* imgPtData1 = imgPtMat1.ptr<Point2f>();
for( i = 0; i < nimages; i++, j += ni )
{
Mat objpt = objectPoints.getMat(i);
Mat imgpt1 = imagePoints1.getMat(i);
ni = objpt.checkVector(3, CV_32F);
int ni1 = imgpt1.checkVector(2, CV_32F);
CV_Assert( ni > 0 && ni == ni1 );
npoints.at<int>(i) = ni;
memcpy( objPtData + j, objpt.data, ni*sizeof(objPtData[0]) );
memcpy( imgPtData1 + j, imgpt1.data, ni*sizeof(imgPtData1[0]) );
if( imgPtData2 )
{
Mat imgpt2 = imagePoints2.getMat(i);
int ni2 = imgpt2.checkVector(2, CV_32F);
CV_Assert( ni == ni2 );
memcpy( imgPtData2 + j, imgpt2.data, ni*sizeof(imgPtData2[0]) );
}
}
}
static Mat prepareCameraMatrix(Mat& cameraMatrix0, int rtype)
{
Mat cameraMatrix = Mat::eye(3, 3, rtype);
if( cameraMatrix0.size() == cameraMatrix.size() )
cameraMatrix0.convertTo(cameraMatrix, rtype);
return cameraMatrix;
}
static Mat prepareDistCoeffs(Mat& distCoeffs0, int rtype)
{
Mat distCoeffs = Mat::zeros(distCoeffs0.cols == 1 ? Size(1, 12) : Size(12, 1), rtype);
if( distCoeffs0.size() == Size(1, 4) ||
distCoeffs0.size() == Size(1, 5) ||
distCoeffs0.size() == Size(1, 8) ||
distCoeffs0.size() == Size(1, 12) ||
distCoeffs0.size() == Size(4, 1) ||
distCoeffs0.size() == Size(5, 1) ||
distCoeffs0.size() == Size(8, 1) ||
distCoeffs0.size() == Size(12, 1) )
{
Mat dstCoeffs(distCoeffs, Rect(0, 0, distCoeffs0.cols, distCoeffs0.rows));
distCoeffs0.convertTo(dstCoeffs, rtype);
}
return distCoeffs;
}
} // namespace cv
void cv::Rodrigues(InputArray _src, OutputArray _dst, OutputArray _jacobian)
{
Mat src = _src.getMat();
bool v2m = src.cols == 1 || src.rows == 1;
_dst.create(3, v2m ? 3 : 1, src.depth());
Mat dst = _dst.getMat();
CvMat _csrc = src, _cdst = dst, _cjacobian;
if( _jacobian.needed() )
{
_jacobian.create(v2m ? Size(9, 3) : Size(3, 9), src.depth());
_cjacobian = _jacobian.getMat();
}
bool ok = cvRodrigues2(&_csrc, &_cdst, _jacobian.needed() ? &_cjacobian : 0) > 0;
if( !ok )
dst = Scalar(0);
}
void cv::matMulDeriv( InputArray _Amat, InputArray _Bmat,
OutputArray _dABdA, OutputArray _dABdB )
{
Mat A = _Amat.getMat(), B = _Bmat.getMat();
_dABdA.create(A.rows*B.cols, A.rows*A.cols, A.type());
_dABdB.create(A.rows*B.cols, B.rows*B.cols, A.type());
CvMat matA = A, matB = B, c_dABdA = _dABdA.getMat(), c_dABdB = _dABdB.getMat();
cvCalcMatMulDeriv(&matA, &matB, &c_dABdA, &c_dABdB);
}
void cv::composeRT( InputArray _rvec1, InputArray _tvec1,
InputArray _rvec2, InputArray _tvec2,
OutputArray _rvec3, OutputArray _tvec3,
OutputArray _dr3dr1, OutputArray _dr3dt1,
OutputArray _dr3dr2, OutputArray _dr3dt2,
OutputArray _dt3dr1, OutputArray _dt3dt1,
OutputArray _dt3dr2, OutputArray _dt3dt2 )
{
Mat rvec1 = _rvec1.getMat(), tvec1 = _tvec1.getMat();
Mat rvec2 = _rvec2.getMat(), tvec2 = _tvec2.getMat();
int rtype = rvec1.type();
_rvec3.create(rvec1.size(), rtype);
_tvec3.create(tvec1.size(), rtype);
Mat rvec3 = _rvec3.getMat(), tvec3 = _tvec3.getMat();
CvMat c_rvec1 = rvec1, c_tvec1 = tvec1, c_rvec2 = rvec2,
c_tvec2 = tvec2, c_rvec3 = rvec3, c_tvec3 = tvec3;
CvMat c_dr3dr1, c_dr3dt1, c_dr3dr2, c_dr3dt2, c_dt3dr1, c_dt3dt1, c_dt3dr2, c_dt3dt2;
CvMat *p_dr3dr1=0, *p_dr3dt1=0, *p_dr3dr2=0, *p_dr3dt2=0, *p_dt3dr1=0, *p_dt3dt1=0, *p_dt3dr2=0, *p_dt3dt2=0;
if( _dr3dr1.needed() )
{
_dr3dr1.create(3, 3, rtype);
p_dr3dr1 = &(c_dr3dr1 = _dr3dr1.getMat());
}
if( _dr3dt1.needed() )
{
_dr3dt1.create(3, 3, rtype);
p_dr3dt1 = &(c_dr3dt1 = _dr3dt1.getMat());
}
if( _dr3dr2.needed() )
{
_dr3dr2.create(3, 3, rtype);
p_dr3dr2 = &(c_dr3dr2 = _dr3dr2.getMat());
}
if( _dr3dt2.needed() )
{
_dr3dt2.create(3, 3, rtype);
p_dr3dt2 = &(c_dr3dt2 = _dr3dt2.getMat());
}
if( _dt3dr1.needed() )
{
_dt3dr1.create(3, 3, rtype);
p_dt3dr1 = &(c_dt3dr1 = _dt3dr1.getMat());
}
if( _dt3dt1.needed() )
{
_dt3dt1.create(3, 3, rtype);
p_dt3dt1 = &(c_dt3dt1 = _dt3dt1.getMat());
}
if( _dt3dr2.needed() )
{
_dt3dr2.create(3, 3, rtype);
p_dt3dr2 = &(c_dt3dr2 = _dt3dr2.getMat());
}
if( _dt3dt2.needed() )
{
_dt3dt2.create(3, 3, rtype);
p_dt3dt2 = &(c_dt3dt2 = _dt3dt2.getMat());
}
cvComposeRT(&c_rvec1, &c_tvec1, &c_rvec2, &c_tvec2, &c_rvec3, &c_tvec3,
p_dr3dr1, p_dr3dt1, p_dr3dr2, p_dr3dt2,
p_dt3dr1, p_dt3dt1, p_dt3dr2, p_dt3dt2);
}
void cv::projectPoints( InputArray _opoints,
InputArray _rvec,
InputArray _tvec,
InputArray _cameraMatrix,
InputArray _distCoeffs,
OutputArray _ipoints,
OutputArray _jacobian,
double aspectRatio )
{
Mat opoints = _opoints.getMat();
int npoints = opoints.checkVector(3), depth = opoints.depth();
CV_Assert(npoints >= 0 && (depth == CV_32F || depth == CV_64F));
CvMat dpdrot, dpdt, dpdf, dpdc, dpddist;
CvMat *pdpdrot=0, *pdpdt=0, *pdpdf=0, *pdpdc=0, *pdpddist=0;
_ipoints.create(npoints, 1, CV_MAKETYPE(depth, 2), -1, true);
CvMat c_imagePoints = _ipoints.getMat();
CvMat c_objectPoints = opoints;
Mat cameraMatrix = _cameraMatrix.getMat();
Mat rvec = _rvec.getMat(), tvec = _tvec.getMat();
CvMat c_cameraMatrix = cameraMatrix;
CvMat c_rvec = rvec, c_tvec = tvec;
double dc0buf[5]={0};
Mat dc0(5,1,CV_64F,dc0buf);
Mat distCoeffs = _distCoeffs.getMat();
if( distCoeffs.empty() )
distCoeffs = dc0;
CvMat c_distCoeffs = distCoeffs;
int ndistCoeffs = distCoeffs.rows + distCoeffs.cols - 1;
if( _jacobian.needed() )
{
_jacobian.create(npoints*2, 3+3+2+2+ndistCoeffs, CV_64F);
Mat jacobian = _jacobian.getMat();
pdpdrot = &(dpdrot = jacobian.colRange(0, 3));
pdpdt = &(dpdt = jacobian.colRange(3, 6));
pdpdf = &(dpdf = jacobian.colRange(6, 8));
pdpdc = &(dpdc = jacobian.colRange(8, 10));
pdpddist = &(dpddist = jacobian.colRange(10, 10+ndistCoeffs));
}
cvProjectPoints2( &c_objectPoints, &c_rvec, &c_tvec, &c_cameraMatrix, &c_distCoeffs,
&c_imagePoints, pdpdrot, pdpdt, pdpdf, pdpdc, pdpddist, aspectRatio );
}
cv::Mat cv::initCameraMatrix2D( InputArrayOfArrays objectPoints,
InputArrayOfArrays imagePoints,
Size imageSize, double aspectRatio )
{
Mat objPt, imgPt, npoints, cameraMatrix(3, 3, CV_64F);
collectCalibrationData( objectPoints, imagePoints, noArray(),
objPt, imgPt, 0, npoints );
CvMat _objPt = objPt, _imgPt = imgPt, _npoints = npoints, _cameraMatrix = cameraMatrix;
cvInitIntrinsicParams2D( &_objPt, &_imgPt, &_npoints,
imageSize, &_cameraMatrix, aspectRatio );
return cameraMatrix;
}
double cv::calibrateCamera( InputArrayOfArrays _objectPoints,
InputArrayOfArrays _imagePoints,
Size imageSize, InputOutputArray _cameraMatrix, InputOutputArray _distCoeffs,
OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, int flags, TermCriteria criteria )
{
int rtype = CV_64F;
Mat cameraMatrix = _cameraMatrix.getMat();
cameraMatrix = prepareCameraMatrix(cameraMatrix, rtype);
Mat distCoeffs = _distCoeffs.getMat();
distCoeffs = prepareDistCoeffs(distCoeffs, rtype);
if( !(flags & CALIB_RATIONAL_MODEL) &&(!(flags & CALIB_THIN_PRISM_MODEL)))
distCoeffs = distCoeffs.rows == 1 ? distCoeffs.colRange(0, 5) : distCoeffs.rowRange(0, 5);
int i;
size_t nimages = _objectPoints.total();
CV_Assert( nimages > 0 );
Mat objPt, imgPt, npoints, rvecM((int)nimages, 3, CV_64FC1), tvecM((int)nimages, 3, CV_64FC1);
collectCalibrationData( _objectPoints, _imagePoints, noArray(),
objPt, imgPt, 0, npoints );
CvMat c_objPt = objPt, c_imgPt = imgPt, c_npoints = npoints;
CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
CvMat c_rvecM = rvecM, c_tvecM = tvecM;
double reprojErr = cvCalibrateCamera2(&c_objPt, &c_imgPt, &c_npoints, imageSize,
&c_cameraMatrix, &c_distCoeffs, &c_rvecM,
&c_tvecM, flags, criteria );
bool rvecs_needed = _rvecs.needed(), tvecs_needed = _tvecs.needed();
if( rvecs_needed )
_rvecs.create((int)nimages, 1, CV_64FC3);
if( tvecs_needed )
_tvecs.create((int)nimages, 1, CV_64FC3);
for( i = 0; i < (int)nimages; i++ )
{
if( rvecs_needed )
{
_rvecs.create(3, 1, CV_64F, i, true);
Mat rv = _rvecs.getMat(i);
memcpy(rv.data, rvecM.ptr<double>(i), 3*sizeof(double));
}
if( tvecs_needed )
{
_tvecs.create(3, 1, CV_64F, i, true);
Mat tv = _tvecs.getMat(i);
memcpy(tv.data, tvecM.ptr<double>(i), 3*sizeof(double));
}
}
cameraMatrix.copyTo(_cameraMatrix);
distCoeffs.copyTo(_distCoeffs);
return reprojErr;
}
void cv::calibrationMatrixValues( InputArray _cameraMatrix, Size imageSize,
double apertureWidth, double apertureHeight,
double& fovx, double& fovy, double& focalLength,
Point2d& principalPoint, double& aspectRatio )
{
Mat cameraMatrix = _cameraMatrix.getMat();
CvMat c_cameraMatrix = cameraMatrix;
cvCalibrationMatrixValues( &c_cameraMatrix, imageSize, apertureWidth, apertureHeight,
&fovx, &fovy, &focalLength, (CvPoint2D64f*)&principalPoint, &aspectRatio );
}
double cv::stereoCalibrate( InputArrayOfArrays _objectPoints,
InputArrayOfArrays _imagePoints1,
InputArrayOfArrays _imagePoints2,
InputOutputArray _cameraMatrix1, InputOutputArray _distCoeffs1,
InputOutputArray _cameraMatrix2, InputOutputArray _distCoeffs2,
Size imageSize, OutputArray _Rmat, OutputArray _Tmat,
OutputArray _Emat, OutputArray _Fmat, int flags ,
TermCriteria criteria)
{
int rtype = CV_64F;
Mat cameraMatrix1 = _cameraMatrix1.getMat();
Mat cameraMatrix2 = _cameraMatrix2.getMat();
Mat distCoeffs1 = _distCoeffs1.getMat();
Mat distCoeffs2 = _distCoeffs2.getMat();
cameraMatrix1 = prepareCameraMatrix(cameraMatrix1, rtype);
cameraMatrix2 = prepareCameraMatrix(cameraMatrix2, rtype);
distCoeffs1 = prepareDistCoeffs(distCoeffs1, rtype);
distCoeffs2 = prepareDistCoeffs(distCoeffs2, rtype);
if( !(flags & CALIB_RATIONAL_MODEL) &&(!(flags & CALIB_THIN_PRISM_MODEL)))
{
distCoeffs1 = distCoeffs1.rows == 1 ? distCoeffs1.colRange(0, 5) : distCoeffs1.rowRange(0, 5);
distCoeffs2 = distCoeffs2.rows == 1 ? distCoeffs2.colRange(0, 5) : distCoeffs2.rowRange(0, 5);
}
_Rmat.create(3, 3, rtype);
_Tmat.create(3, 1, rtype);
Mat objPt, imgPt, imgPt2, npoints;
collectCalibrationData( _objectPoints, _imagePoints1, _imagePoints2,
objPt, imgPt, &imgPt2, npoints );
CvMat c_objPt = objPt, c_imgPt = imgPt, c_imgPt2 = imgPt2, c_npoints = npoints;
CvMat c_cameraMatrix1 = cameraMatrix1, c_distCoeffs1 = distCoeffs1;
CvMat c_cameraMatrix2 = cameraMatrix2, c_distCoeffs2 = distCoeffs2;
CvMat c_matR = _Rmat.getMat(), c_matT = _Tmat.getMat(), c_matE, c_matF, *p_matE = 0, *p_matF = 0;
if( _Emat.needed() )
{
_Emat.create(3, 3, rtype);
p_matE = &(c_matE = _Emat.getMat());
}
if( _Fmat.needed() )
{
_Fmat.create(3, 3, rtype);
p_matF = &(c_matF = _Fmat.getMat());
}
double err = cvStereoCalibrate(&c_objPt, &c_imgPt, &c_imgPt2, &c_npoints, &c_cameraMatrix1,
&c_distCoeffs1, &c_cameraMatrix2, &c_distCoeffs2, imageSize,
&c_matR, &c_matT, p_matE, p_matF, flags, criteria );
cameraMatrix1.copyTo(_cameraMatrix1);
cameraMatrix2.copyTo(_cameraMatrix2);
distCoeffs1.copyTo(_distCoeffs1);
distCoeffs2.copyTo(_distCoeffs2);
return err;
}
void cv::stereoRectify( InputArray _cameraMatrix1, InputArray _distCoeffs1,
InputArray _cameraMatrix2, InputArray _distCoeffs2,
Size imageSize, InputArray _Rmat, InputArray _Tmat,
OutputArray _Rmat1, OutputArray _Rmat2,
OutputArray _Pmat1, OutputArray _Pmat2,
OutputArray _Qmat, int flags,
double alpha, Size newImageSize,
Rect* validPixROI1, Rect* validPixROI2 )
{
Mat cameraMatrix1 = _cameraMatrix1.getMat(), cameraMatrix2 = _cameraMatrix2.getMat();
Mat distCoeffs1 = _distCoeffs1.getMat(), distCoeffs2 = _distCoeffs2.getMat();
Mat Rmat = _Rmat.getMat(), Tmat = _Tmat.getMat();
CvMat c_cameraMatrix1 = cameraMatrix1;
CvMat c_cameraMatrix2 = cameraMatrix2;
CvMat c_distCoeffs1 = distCoeffs1;
CvMat c_distCoeffs2 = distCoeffs2;
CvMat c_R = Rmat, c_T = Tmat;
int rtype = CV_64F;
_Rmat1.create(3, 3, rtype);
_Rmat2.create(3, 3, rtype);
_Pmat1.create(3, 4, rtype);
_Pmat2.create(3, 4, rtype);
CvMat c_R1 = _Rmat1.getMat(), c_R2 = _Rmat2.getMat(), c_P1 = _Pmat1.getMat(), c_P2 = _Pmat2.getMat();
CvMat c_Q, *p_Q = 0;
if( _Qmat.needed() )
{
_Qmat.create(4, 4, rtype);
p_Q = &(c_Q = _Qmat.getMat());
}
cvStereoRectify( &c_cameraMatrix1, &c_cameraMatrix2, &c_distCoeffs1, &c_distCoeffs2,
imageSize, &c_R, &c_T, &c_R1, &c_R2, &c_P1, &c_P2, p_Q, flags, alpha,
newImageSize, (CvRect*)validPixROI1, (CvRect*)validPixROI2);
}
bool cv::stereoRectifyUncalibrated( InputArray _points1, InputArray _points2,
InputArray _Fmat, Size imgSize,
OutputArray _Hmat1, OutputArray _Hmat2, double threshold )
{
int rtype = CV_64F;
_Hmat1.create(3, 3, rtype);
_Hmat2.create(3, 3, rtype);
Mat F = _Fmat.getMat();
Mat points1 = _points1.getMat(), points2 = _points2.getMat();
CvMat c_pt1 = points1, c_pt2 = points2;
CvMat c_F, *p_F=0, c_H1 = _Hmat1.getMat(), c_H2 = _Hmat2.getMat();
if( F.size() == Size(3, 3) )
p_F = &(c_F = F);
return cvStereoRectifyUncalibrated(&c_pt1, &c_pt2, p_F, imgSize, &c_H1, &c_H2, threshold) > 0;
}
cv::Mat cv::getOptimalNewCameraMatrix( InputArray _cameraMatrix,
InputArray _distCoeffs,
Size imgSize, double alpha, Size newImgSize,
Rect* validPixROI, bool centerPrincipalPoint )
{
Mat cameraMatrix = _cameraMatrix.getMat(), distCoeffs = _distCoeffs.getMat();
CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
Mat newCameraMatrix(3, 3, CV_MAT_TYPE(c_cameraMatrix.type));
CvMat c_newCameraMatrix = newCameraMatrix;
cvGetOptimalNewCameraMatrix(&c_cameraMatrix, &c_distCoeffs, imgSize,
alpha, &c_newCameraMatrix,
newImgSize, (CvRect*)validPixROI, (int)centerPrincipalPoint);
return newCameraMatrix;
}
cv::Vec3d cv::RQDecomp3x3( InputArray _Mmat,
OutputArray _Rmat,
OutputArray _Qmat,
OutputArray _Qx,
OutputArray _Qy,
OutputArray _Qz )
{
Mat M = _Mmat.getMat();
_Rmat.create(3, 3, M.type());
_Qmat.create(3, 3, M.type());
Vec3d eulerAngles;
CvMat matM = M, matR = _Rmat.getMat(), matQ = _Qmat.getMat(), Qx, Qy, Qz, *pQx=0, *pQy=0, *pQz=0;
if( _Qx.needed() )
{
_Qx.create(3, 3, M.type());
pQx = &(Qx = _Qx.getMat());
}
if( _Qy.needed() )
{
_Qy.create(3, 3, M.type());
pQy = &(Qy = _Qy.getMat());
}
if( _Qz.needed() )
{
_Qz.create(3, 3, M.type());
pQz = &(Qz = _Qz.getMat());
}
cvRQDecomp3x3(&matM, &matR, &matQ, pQx, pQy, pQz, (CvPoint3D64f*)&eulerAngles[0]);
return eulerAngles;
}
void cv::decomposeProjectionMatrix( InputArray _projMatrix, OutputArray _cameraMatrix,
OutputArray _rotMatrix, OutputArray _transVect,
OutputArray _rotMatrixX, OutputArray _rotMatrixY,
OutputArray _rotMatrixZ, OutputArray _eulerAngles )
{
Mat projMatrix = _projMatrix.getMat();
int type = projMatrix.type();
_cameraMatrix.create(3, 3, type);
_rotMatrix.create(3, 3, type);
_transVect.create(4, 1, type);
CvMat c_projMatrix = projMatrix, c_cameraMatrix = _cameraMatrix.getMat();
CvMat c_rotMatrix = _rotMatrix.getMat(), c_transVect = _transVect.getMat();
CvMat c_rotMatrixX, *p_rotMatrixX = 0;
CvMat c_rotMatrixY, *p_rotMatrixY = 0;
CvMat c_rotMatrixZ, *p_rotMatrixZ = 0;
CvPoint3D64f *p_eulerAngles = 0;
if( _rotMatrixX.needed() )
{
_rotMatrixX.create(3, 3, type);
p_rotMatrixX = &(c_rotMatrixX = _rotMatrixX.getMat());
}
if( _rotMatrixY.needed() )
{
_rotMatrixY.create(3, 3, type);
p_rotMatrixY = &(c_rotMatrixY = _rotMatrixY.getMat());
}
if( _rotMatrixZ.needed() )
{
_rotMatrixZ.create(3, 3, type);
p_rotMatrixZ = &(c_rotMatrixZ = _rotMatrixZ.getMat());
}
if( _eulerAngles.needed() )
{
_eulerAngles.create(3, 1, CV_64F, -1, true);
p_eulerAngles = (CvPoint3D64f*)_eulerAngles.getMat().data;
}
cvDecomposeProjectionMatrix(&c_projMatrix, &c_cameraMatrix, &c_rotMatrix,
&c_transVect, p_rotMatrixX, p_rotMatrixY,
p_rotMatrixZ, p_eulerAngles);
}
namespace cv
{
static void adjust3rdMatrix(InputArrayOfArrays _imgpt1_0,
InputArrayOfArrays _imgpt3_0,
const Mat& cameraMatrix1, const Mat& distCoeffs1,
const Mat& cameraMatrix3, const Mat& distCoeffs3,
const Mat& R1, const Mat& R3, const Mat& P1, Mat& P3 )
{
size_t n1 = _imgpt1_0.total(), n3 = _imgpt3_0.total();
std::vector<Point2f> imgpt1, imgpt3;
for( int i = 0; i < (int)std::min(n1, n3); i++ )
{
Mat pt1 = _imgpt1_0.getMat(i), pt3 = _imgpt3_0.getMat(i);
int ni1 = pt1.checkVector(2, CV_32F), ni3 = pt3.checkVector(2, CV_32F);
CV_Assert( ni1 > 0 && ni1 == ni3 );
const Point2f* pt1data = pt1.ptr<Point2f>();
const Point2f* pt3data = pt3.ptr<Point2f>();
std::copy(pt1data, pt1data + ni1, std::back_inserter(imgpt1));
std::copy(pt3data, pt3data + ni3, std::back_inserter(imgpt3));
}
undistortPoints(imgpt1, imgpt1, cameraMatrix1, distCoeffs1, R1, P1);
undistortPoints(imgpt3, imgpt3, cameraMatrix3, distCoeffs3, R3, P3);
double y1_ = 0, y2_ = 0, y1y1_ = 0, y1y2_ = 0;
size_t n = imgpt1.size();
for( size_t i = 0; i < n; i++ )
{
double y1 = imgpt3[i].y, y2 = imgpt1[i].y;
y1_ += y1; y2_ += y2;
y1y1_ += y1*y1; y1y2_ += y1*y2;
}
y1_ /= n;
y2_ /= n;
y1y1_ /= n;
y1y2_ /= n;
double a = (y1y2_ - y1_*y2_)/(y1y1_ - y1_*y1_);
double b = y2_ - a*y1_;
P3.at<double>(0,0) *= a;
P3.at<double>(1,1) *= a;
P3.at<double>(0,2) = P3.at<double>(0,2)*a;
P3.at<double>(1,2) = P3.at<double>(1,2)*a + b;
P3.at<double>(0,3) *= a;
P3.at<double>(1,3) *= a;
}
}
float cv::rectify3Collinear( InputArray _cameraMatrix1, InputArray _distCoeffs1,
InputArray _cameraMatrix2, InputArray _distCoeffs2,
InputArray _cameraMatrix3, InputArray _distCoeffs3,
InputArrayOfArrays _imgpt1,
InputArrayOfArrays _imgpt3,
Size imageSize, InputArray _Rmat12, InputArray _Tmat12,
InputArray _Rmat13, InputArray _Tmat13,
OutputArray _Rmat1, OutputArray _Rmat2, OutputArray _Rmat3,
OutputArray _Pmat1, OutputArray _Pmat2, OutputArray _Pmat3,
OutputArray _Qmat,
double alpha, Size newImgSize,
Rect* roi1, Rect* roi2, int flags )
{
// first, rectify the 1-2 stereo pair
stereoRectify( _cameraMatrix1, _distCoeffs1, _cameraMatrix2, _distCoeffs2,
imageSize, _Rmat12, _Tmat12, _Rmat1, _Rmat2, _Pmat1, _Pmat2, _Qmat,
flags, alpha, newImgSize, roi1, roi2 );
Mat R12 = _Rmat12.getMat(), R13 = _Rmat13.getMat(), T12 = _Tmat12.getMat(), T13 = _Tmat13.getMat();
_Rmat3.create(3, 3, CV_64F);
_Pmat3.create(3, 4, CV_64F);
Mat P1 = _Pmat1.getMat(), P2 = _Pmat2.getMat();
Mat R3 = _Rmat3.getMat(), P3 = _Pmat3.getMat();
// recompute rectification transforms for cameras 1 & 2.
Mat om, r_r, r_r13;
if( R13.size() != Size(3,3) )
Rodrigues(R13, r_r13);
else
R13.copyTo(r_r13);
if( R12.size() == Size(3,3) )
Rodrigues(R12, om);
else
R12.copyTo(om);
om *= -0.5;
Rodrigues(om, r_r); // rotate cameras to same orientation by averaging
Mat_<double> t12 = r_r * T12;
int idx = fabs(t12(0,0)) > fabs(t12(1,0)) ? 0 : 1;
double c = t12(idx,0), nt = norm(t12, CV_L2);
Mat_<double> uu = Mat_<double>::zeros(3,1);
uu(idx, 0) = c > 0 ? 1 : -1;
// calculate global Z rotation
Mat_<double> ww = t12.cross(uu), wR;
double nw = norm(ww, CV_L2);
ww *= acos(fabs(c)/nt)/nw;
Rodrigues(ww, wR);
// now rotate camera 3 to make its optical axis parallel to cameras 1 and 2.
R3 = wR*r_r.t()*r_r13.t();
Mat_<double> t13 = R3 * T13;
P2.copyTo(P3);
Mat t = P3.col(3);
t13.copyTo(t);
P3.at<double>(0,3) *= P3.at<double>(0,0);
P3.at<double>(1,3) *= P3.at<double>(1,1);
if( !_imgpt1.empty() && _imgpt3.empty() )
adjust3rdMatrix(_imgpt1, _imgpt3, _cameraMatrix1.getMat(), _distCoeffs1.getMat(),
_cameraMatrix3.getMat(), _distCoeffs3.getMat(), _Rmat1.getMat(), R3, P1, P3);
return (float)((P3.at<double>(idx,3)/P3.at<double>(idx,idx))/
(P2.at<double>(idx,3)/P2.at<double>(idx,idx)));
}
/* End of file. */