bool Epipolar::isValidPair(vector<DMatch>& matches, vector<KeyPoint>& key1, vector<KeyPoint>& key2, Mat& cam, Mat& distor, Mat& ess, Mat& inliersMask, double inlierPercent){
vector<Point2f>pts1, pts2;
inliersMask.deallocate();
Mat rot, trans;
size_t n = matches.size();
Utility:: getPointMatches(key1, key2, matches, pts1, pts2);
undistortPoints(pts1, pts1, cam, distor);
undistortPoints(pts2, pts2, cam, distor);
ess = findEssentialMat(pts1, pts2, 1.0, Point(0, 0), RANSAC, 0.999, 1.25, inliersMask);
int inliers = recoverPose(ess, pts1, pts2, rot, trans, 1.0, Point(0, 0), inliersMask);
return ((double)inliers / n) > inlierPercent;
}
void Calibration::undistort(vector<ofVec2f>& src, vector<ofVec2f>& dst) const {
int n = src.size();
dst.resize(n);
Mat matSrc = Mat(n, 1, CV_32FC2, &src[0].x);
Mat matDst = Mat(n, 1, CV_32FC2, &dst[0].x);
undistortPoints(matSrc, matDst, distortedIntrinsics.getCameraMatrix(), distCoeffs);
}
ofVec2f Calibration::undistort(ofVec2f& src) const {
ofVec2f dst;
Mat matSrc = Mat(1, 1, CV_32FC2, &src.x);
Mat matDst = Mat(1, 1, CV_32FC2, &dst.x);;
undistortPoints(matSrc, matDst, distortedIntrinsics.getCameraMatrix(), distCoeffs);
return dst;
}
void Epipolar::calcEssMatrix(vector<DMatch>& goodMatches, vector<KeyPoint>& keys1, vector<KeyPoint>& keys2, Mat& cam, Mat& distor, Mat& ess, double inlierPercent){
int inliers = 0;
vector<Point2f>pts1, pts2;
Mat rot, trans, inlierMask;
size_t n = goodMatches.size();
for (size_t j = 0; j < n; j++)
{
pts1.push_back(keys1[goodMatches[j].trainIdx].pt);
pts2.push_back(keys2[goodMatches[j].queryIdx].pt);
}
undistortPoints(pts1, pts1, cam, distor);
undistortPoints(pts2, pts2, cam, distor);
ess = findEssentialMat(pts1, pts2, 1.0, Point(0, 0), RANSAC, 0.999, 1.25, inlierMask);
inliers = recoverPose(ess, pts1, pts2, rot, trans, 1.0, Point(0, 0), inlierMask);
if ((double)inliers / n < inlierPercent){
ess.release();
}
}
double CameraCalibration::FundamentalMatrixQuality(vector<vector<Point2f> > LeftImagePoints, vector<vector<Point2f> > RightImagePoints,
Mat LeftCameraMatrix, Mat RightCameraMatrix, Mat LeftDistCoeffs, Mat RightDistCoeffs, Mat F)
{
// CALIBRATION QUALITY CHECK
// because the output fundamental matrix implicitly
// includes all the output information,
// we can check the quality of calibration using the
// epipolar geometry constraint: m2^t*F*m1=0
double err = 0;
int npoints = 0;
vector<Vec3f> lines[2];
for(int i = 0; i < NumFrames; i++ )
{
int npt = (int)LeftImagePoints[i].size();
Mat imgpt[2];
imgpt[0] = Mat(LeftImagePoints[i]);
imgpt[1] = Mat(RightImagePoints[i]);
undistortPoints(imgpt[0], imgpt[0], LeftCameraMatrix, LeftDistCoeffs, Mat(), LeftCameraMatrix);
undistortPoints(imgpt[1], imgpt[1], RightCameraMatrix, RightDistCoeffs, Mat(), RightCameraMatrix);
computeCorrespondEpilines(imgpt[0], 1, F, lines[0]);
computeCorrespondEpilines(imgpt[1], 2, F, lines[1]);
for(int j = 0; j < npt; j++ )
{
double errij = fabs(LeftImagePoints[i][j].x*lines[1][j][0] +
LeftImagePoints[i][j].y*lines[1][j][1] + lines[1][j][2]) +
fabs(RightImagePoints[i][j].x*lines[0][j][0] +
RightImagePoints[i][j].y*lines[0][j][1] + lines[0][j][2]);
err += errij;
}
npoints += npt;
}
return err/npoints;
}
int solveP3P( InputArray _opoints, InputArray _ipoints,
InputArray _cameraMatrix, InputArray _distCoeffs,
OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs, int flags) {
CV_INSTRUMENT_REGION();
Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
CV_Assert( npoints == 3 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) );
CV_Assert( flags == SOLVEPNP_P3P || flags == SOLVEPNP_AP3P );
Mat cameraMatrix0 = _cameraMatrix.getMat();
Mat distCoeffs0 = _distCoeffs.getMat();
Mat cameraMatrix = Mat_<double>(cameraMatrix0);
Mat distCoeffs = Mat_<double>(distCoeffs0);
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
std::vector<Mat> Rs, ts;
int solutions = 0;
if (flags == SOLVEPNP_P3P)
{
p3p P3Psolver(cameraMatrix);
solutions = P3Psolver.solve(Rs, ts, opoints, undistortedPoints);
}
else if (flags == SOLVEPNP_AP3P)
{
ap3p P3Psolver(cameraMatrix);
solutions = P3Psolver.solve(Rs, ts, opoints, undistortedPoints);
}
if (solutions == 0) {
return 0;
}
if (_rvecs.needed()) {
_rvecs.create(solutions, 1, CV_64F);
}
if (_tvecs.needed()) {
_tvecs.create(solutions, 1, CV_64F);
}
for (int i = 0; i < solutions; i++) {
Mat rvec;
Rodrigues(Rs[i], rvec);
_tvecs.getMatRef(i) = ts[i];
_rvecs.getMatRef(i) = rvec;
}
return solutions;
}
void Calibration::undistort(vector<ofVec2f> &src, vector<ofVec2f> &dst)
{
int nPoints = src.size();
if (dst.size() != nPoints)
dst.resize(src.size());
Mat matSrc = Mat(nPoints, 1, CV_32FC2, &src[0].x);
Mat matDst = Mat(nPoints, 1, CV_32FC2, &dst[0].x);
undistortPoints(matSrc, matDst, distortedIntrinsics.getCameraMatrix(), distCoeffs);
}
// Algorithm:
// plane equation: P*N + c = 0
// we find point rays in 3D from image points and camera parameters
// then we fit c by minimizing average L2 distance between rotated and translated object points
// and points found by crossing point rays with plane. We use the fact that center of mass
// of object points and fitted points should coincide.
void findPlanarObjectPose(const vector<Point3f>& _object_points, const Mat& image_points, const Point3f& normal,
const Mat& intrinsic_matrix, const Mat& distortion_coeffs, double& alpha, double& C, vector<Point3f>& object_points_crf)
{
vector<Point2f> _rays;
undistortPoints(image_points, _rays, intrinsic_matrix, distortion_coeffs);
// filter out rays that are parallel to the plane
vector<Point3f> rays;
vector<Point3f> object_points;
for(size_t i = 0; i < _rays.size(); i++)
{
Point3f ray(_rays[i].x, _rays[i].y, 1.0f);
double proj = ray.dot(normal);
if(fabs(proj) > std::numeric_limits<double>::epsilon())
{
rays.push_back(ray*(1.0/ray.dot(normal)));
object_points.push_back(_object_points[i]);
}
}
Point3f pc = massCenter(rays);
Point3f p0c = massCenter(object_points);
vector<Point3f> drays;
drays.resize(rays.size());
for(size_t i = 0; i < rays.size(); i++)
{
drays[i] = rays[i] - pc;
object_points[i] -= p0c;
}
double s1 = 0.0, s2 = 0.0, s3 = 0.0;
for(size_t i = 0; i < rays.size(); i++)
{
Point3f vprod = crossProduct(drays[i], object_points[i]);
s1 += vprod.dot(normal);
s2 += drays[i].dot(object_points[i]);
s3 += drays[i].dot(drays[i]);
}
alpha = atan2(s1, s2);
C = (s2*cos(alpha) + s1*sin(alpha))/s3;
// printf("alpha = %f, C = %f\n", alpha, C);
object_points_crf.resize(rays.size());
for(size_t i = 0; i < rays.size(); i++)
{
object_points_crf[i] = rays[i]*C;
}
}
void PositionCalculatorImpl::addMeasurementImpl( InputArray _tvec, InputArray _rvec, const Point2f _pt
, double /*time*/,
InputArray _cameraMatrix, InputArray _distortionMatrix )
{
Mat tvec = _tvec.getMat();
Mat rvec = _rvec.getMat();
Mat camera_matrix = _cameraMatrix.getMat();
const Mat distortion_matrix = _distortionMatrix.getMat();
std::vector< Point2f > pts_in, pts_out;
pts_in.push_back( _pt );
undistortPoints( pts_in, pts_out, camera_matrix, distortion_matrix, noArray(), camera_matrix );
Mat los( 3, 1,CV_64F );
los.at< double >( 0 ) = pts_out[0].x;
los.at< double >( 1 ) = pts_out[0].y;
los.at< double >( 2 ) = 1;
if ( camera_matrix.type() != CV_64F )
camera_matrix.convertTo( camera_matrix, CV_64F );
if ( rvec.type() != CV_64F )
rvec.convertTo( rvec, CV_64F );
if ( tvec.type() != CV_64F )
tvec.convertTo( tvec, CV_64F );
los = camera_matrix.inv() * los;
Mat camera_rotation;
if ( rvec.rows == 3 && rvec.cols == 3 )
camera_rotation = rvec;
else
Rodrigues( rvec, camera_rotation );
if(tvec.rows == 1)
tvec = tvec.t();
camera_rotation = camera_rotation.t();
const Mat camera_translation = ( -camera_rotation * tvec );
los = camera_rotation * los;
positions.push_back( camera_translation );
Mat zero_pos( 3, 1, CV_64F );
zero_pos.setTo( 0 );
const Point2d azel = getAzEl( zero_pos, los );
angles.push_back( azel );
}
void stereoCalibThread::stereoCalibration(const vector<string>& imagelist, int boardWidth, int boardHeight,float sqsize)
{
Size boardSize;
boardSize.width=boardWidth;
boardSize.height=boardHeight;
if( imagelist.size() % 2 != 0 )
{
cout << "Error: the image list contains odd (non-even) number of elements\n";
return;
}
const int maxScale = 2;
// ARRAY AND VECTOR STORAGE:
std::vector<std::vector<Point2f> > imagePoints[2];
std::vector<std::vector<Point3f> > objectPoints;
Size imageSize;
int i, j, k, nimages = (int)imagelist.size()/2;
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
std::vector<string> goodImageList;
for( i = j = 0; i < nimages; i++ )
{
for( k = 0; k < 2; k++ )
{
const string& filename = imagelist[i*2+k];
Mat img = cv::imread(filename, 0);
if(img.empty())
break;
if( imageSize == Size() )
imageSize = img.size();
else if( img.size() != imageSize )
{
cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n";
break;
}
bool found = false;
std::vector<Point2f>& corners = imagePoints[k][j];
for( int scale = 1; scale <= maxScale; scale++ )
{
Mat timg;
if( scale == 1 )
timg = img;
else
resize(img, timg, Size(), scale, scale);
if(boardType == "CIRCLES_GRID") {
found = findCirclesGridDefault(timg, boardSize, corners, CALIB_CB_SYMMETRIC_GRID | CALIB_CB_CLUSTERING);
} else if(boardType == "ASYMMETRIC_CIRCLES_GRID") {
found = findCirclesGridDefault(timg, boardSize, corners, CALIB_CB_ASYMMETRIC_GRID | CALIB_CB_CLUSTERING);
} else {
found = findChessboardCorners(timg, boardSize, corners,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_NORMALIZE_IMAGE);
}
if( found )
{
if( scale > 1 )
{
Mat cornersMat(corners);
cornersMat *= 1./scale;
}
break;
}
}
if( !found )
break;
}
if( k == 2 )
{
goodImageList.push_back(imagelist[i*2]);
goodImageList.push_back(imagelist[i*2+1]);
j++;
}
}
fprintf(stdout,"%i pairs have been successfully detected.\n",j);
nimages = j;
if( nimages < 2 )
{
fprintf(stdout,"Error: too few pairs detected \n");
return;
}
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
objectPoints.resize(nimages);
for( i = 0; i < nimages; i++ )
{
for( j = 0; j < boardSize.height; j++ )
for( k = 0; k < boardSize.width; k++ )
objectPoints[i].push_back(Point3f(j*squareSize, k*squareSize, 0));
}
fprintf(stdout,"Running stereo calibration ...\n");
Mat cameraMatrix[2], distCoeffs[2];
Mat E, F;
if(this->Kleft.empty() || this->Kright.empty())
{
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
this->Kleft, this->DistL,
this->Kright, this->DistR,
imageSize, this->R, this->T, E, F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),
CV_CALIB_FIX_ASPECT_RATIO +
CV_CALIB_ZERO_TANGENT_DIST +
CV_CALIB_SAME_FOCAL_LENGTH +
CV_CALIB_FIX_K3);
fprintf(stdout,"done with RMS error= %f\n",rms);
} else
{
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
this->Kleft, this->DistL,
this->Kright, this->DistR,
imageSize, this->R, this->T, E, F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),CV_CALIB_FIX_ASPECT_RATIO + CV_CALIB_FIX_INTRINSIC + CV_CALIB_FIX_K3);
fprintf(stdout,"done with RMS error= %f\n",rms);
}
// CALIBRATION QUALITY CHECK
cameraMatrix[0] = this->Kleft;
cameraMatrix[1] = this->Kright;
distCoeffs[0]=this->DistL;
distCoeffs[1]=this->DistR;
Mat R, T;
T=this->T;
R=this->R;
double err = 0;
int npoints = 0;
std::vector<Vec3f> lines[2];
for( i = 0; i < nimages; i++ )
{
int npt = (int)imagePoints[0][i].size();
Mat imgpt[2];
for( k = 0; k < 2; k++ )
{
imgpt[k] = Mat(imagePoints[k][i]);
undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]);
computeCorrespondEpilines(imgpt[k], k+1, F, lines[k]);
}
for( j = 0; j < npt; j++ )
{
double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] +
imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) +
fabs(imagePoints[1][i][j].x*lines[0][j][0] +
imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]);
err += errij;
}
npoints += npt;
}
fprintf(stdout,"average reprojection err = %f\n",err/npoints);
cout.flush();
}
bool solvePnP( InputArray _opoints, InputArray _ipoints,
InputArray _cameraMatrix, InputArray _distCoeffs,
OutputArray _rvec, OutputArray _tvec, bool useExtrinsicGuess, int flags )
{
CV_INSTRUMENT_REGION()
Mat opoints = _opoints.getMat(), ipoints = _ipoints.getMat();
int npoints = std::max(opoints.checkVector(3, CV_32F), opoints.checkVector(3, CV_64F));
CV_Assert( npoints >= 0 && npoints == std::max(ipoints.checkVector(2, CV_32F), ipoints.checkVector(2, CV_64F)) );
Mat rvec, tvec;
if( flags != SOLVEPNP_ITERATIVE )
useExtrinsicGuess = false;
if( useExtrinsicGuess )
{
int rtype = _rvec.type(), ttype = _tvec.type();
Size rsize = _rvec.size(), tsize = _tvec.size();
CV_Assert( (rtype == CV_32F || rtype == CV_64F) &&
(ttype == CV_32F || ttype == CV_64F) );
CV_Assert( (rsize == Size(1, 3) || rsize == Size(3, 1)) &&
(tsize == Size(1, 3) || tsize == Size(3, 1)) );
}
else
{
int mtype = CV_64F;
// use CV_32F if all PnP inputs are CV_32F and outputs are empty
if (_ipoints.depth() == _cameraMatrix.depth() && _ipoints.depth() == _opoints.depth() &&
_rvec.empty() && _tvec.empty())
mtype = _opoints.depth();
_rvec.create(3, 1, mtype);
_tvec.create(3, 1, mtype);
}
rvec = _rvec.getMat();
tvec = _tvec.getMat();
Mat cameraMatrix0 = _cameraMatrix.getMat();
Mat distCoeffs0 = _distCoeffs.getMat();
Mat cameraMatrix = Mat_<double>(cameraMatrix0);
Mat distCoeffs = Mat_<double>(distCoeffs0);
bool result = false;
if (flags == SOLVEPNP_EPNP || flags == SOLVEPNP_DLS || flags == SOLVEPNP_UPNP)
{
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
epnp PnP(cameraMatrix, opoints, undistortedPoints);
Mat R;
PnP.compute_pose(R, tvec);
Rodrigues(R, rvec);
result = true;
}
else if (flags == SOLVEPNP_P3P)
{
CV_Assert( npoints == 4);
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
p3p P3Psolver(cameraMatrix);
Mat R;
result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
if (result)
Rodrigues(R, rvec);
}
else if (flags == SOLVEPNP_AP3P)
{
CV_Assert( npoints == 4);
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
ap3p P3Psolver(cameraMatrix);
Mat R;
result = P3Psolver.solve(R, tvec, opoints, undistortedPoints);
if (result)
Rodrigues(R, rvec);
}
else if (flags == SOLVEPNP_ITERATIVE)
{
CvMat c_objectPoints = opoints, c_imagePoints = ipoints;
CvMat c_cameraMatrix = cameraMatrix, c_distCoeffs = distCoeffs;
CvMat c_rvec = rvec, c_tvec = tvec;
cvFindExtrinsicCameraParams2(&c_objectPoints, &c_imagePoints, &c_cameraMatrix,
c_distCoeffs.rows*c_distCoeffs.cols ? &c_distCoeffs : 0,
&c_rvec, &c_tvec, useExtrinsicGuess );
result = true;
}
/*else if (flags == SOLVEPNP_DLS)
{
Mat undistortedPoints;
undistortPoints(ipoints, undistortedPoints, cameraMatrix, distCoeffs);
dls PnP(opoints, undistortedPoints);
Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
bool result = PnP.compute_pose(R, tvec);
if (result)
Rodrigues(R, rvec);
return result;
}
else if (flags == SOLVEPNP_UPNP)
{
upnp PnP(cameraMatrix, opoints, ipoints);
Mat R, rvec = _rvec.getMat(), tvec = _tvec.getMat();
PnP.compute_pose(R, tvec);
Rodrigues(R, rvec);
return true;
}*/
else
CV_Error(CV_StsBadArg, "The flags argument must be one of SOLVEPNP_ITERATIVE, SOLVEPNP_P3P, SOLVEPNP_EPNP or SOLVEPNP_DLS");
return result;
}
/// Calibrates the extrinsic parameters of the setup and saves it to an XML file
/// Press'r' to retreive chessboard corners
/// 's' to save and exit
/// 'c' to exit without saving
/// In: inputCapture1: video feed of camera 1
/// inputCapture2: video feed of camera 2
void CalibrateEnvironment(VideoCapture& inputCapture1, VideoCapture& inputCapture2)
{
Size boardSize;
boardSize.width = BOARD_WIDTH;
boardSize.height = BOARD_HEIGHT;
const string fileName1 = "CameraIntrinsics1.xml";
const string fileName2 = "CameraIntrinsics2.xml";
cerr << "Attempting to open configuration files" << endl;
FileStorage fs1(fileName1, FileStorage::READ);
FileStorage fs2(fileName2, FileStorage::READ);
Mat cameraMatrix1, cameraMatrix2;
Mat distCoeffs1, distCoeffs2;
fs1["Camera_Matrix"] >> cameraMatrix1;
fs1["Distortion_Coefficients"] >> distCoeffs1;
fs2["Camera_Matrix"] >> cameraMatrix2;
fs2["Distortion_Coefficients"] >> distCoeffs2;
if (cameraMatrix1.data == NULL || distCoeffs1.data == NULL ||
cameraMatrix2.data == NULL || distCoeffs2.data == NULL)
{
cerr << "Could not load camera intrinsics\n" << endl;
}
else{
cerr << "Loaded intrinsics\n" << endl;
cerr << "Camera Matrix1: " << cameraMatrix1 << endl;
cerr << "Camera Matrix2: " << cameraMatrix2 << endl;
}
Mat translation;
Mat image1, image2;
Mat mapX1, mapX2, mapY1, mapY2;
inputCapture1.read(image1);
Size imageSize = image1.size();
bool rotationCalibrated = false;
while(inputCapture1.isOpened() && inputCapture2.isOpened())
{
inputCapture1.read(image1);
inputCapture2.read(image2);
if (rotationCalibrated)
{
Mat t1 = image1.clone();
Mat t2 = image2.clone();
remap(t1, image1, mapX1, mapY1, INTER_LINEAR);
remap(t2, image2, mapX2, mapY2, INTER_LINEAR);
t1.release();
t2.release();
}
char c = waitKey(15);
if (c == 'c')
{
cerr << "Cancelling..." << endl;
return;
}
else if(c == 's' && rotationCalibrated)
{
cerr << "Saving..." << endl;
const string fileName = "EnvironmentCalibration.xml";
FileStorage fs(fileName, FileStorage::WRITE);
fs << "Camera_Matrix_1" << getOptimalNewCameraMatrix(cameraMatrix1, distCoeffs1, imageSize, 1,imageSize, 0);
fs << "Camera_Matrix_2" << getOptimalNewCameraMatrix(cameraMatrix2, distCoeffs2, imageSize, 1, imageSize, 0);
fs << "Mapping_X_1" << mapX1;
fs << "Mapping_Y_1" << mapY1;
fs << "Mapping_X_2" << mapX2;
fs << "Mapping_Y_2" << mapY2;
fs << "Translation" << translation;
cerr << "Exiting..." << endl;
destroyAllWindows();
return;
}
else if(c == 's' && !rotationCalibrated)
{
cerr << "Exiting..." << endl;
destroyAllWindows();
return;
}
else if (c == 'r')
{
BoardSettings s;
s.boardSize.width = BOARD_WIDTH;
s.boardSize.height = BOARD_HEIGHT;
s.cornerNum = s.boardSize.width * s.boardSize.height;
s.squareSize = (float)SQUARE_SIZE;
vector<Point3f> objectPoints;
vector<vector<Point2f> > imagePoints1, imagePoints2;
if (RetrieveChessboardCorners(imagePoints1, imagePoints2, s, inputCapture1, inputCapture2, ITERATIONS))
{
vector<vector<Point3f> > objectPoints(1);
CalcBoardCornerPositions(s.boardSize, s.squareSize, objectPoints[0]);
objectPoints.resize(imagePoints1.size(),objectPoints[0]);
Mat R, T, E, F;
Mat rmat1, rmat2, rvec;
double rms = stereoCalibrate(objectPoints, imagePoints1, imagePoints2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, imageSize, R, T, E, F,
TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 1000, 0.01),
CV_CALIB_FIX_INTRINSIC);
cerr << "Original translation: " << T << endl;
cerr << "Reprojection error reported by camera: " << rms << endl;
// convert to rotation vector and then remove 90 degree offset
Rodrigues(R, rvec);
rvec.at<double>(1,0) -= 1.570796327;
// equal rotation applied to each image...not necessarily needed
rvec = rvec/2;
Rodrigues(rvec, rmat1);
invert(rmat1,rmat2);
initUndistortRectifyMap(cameraMatrix1, distCoeffs1, rmat1,
getOptimalNewCameraMatrix(cameraMatrix1, distCoeffs1, imageSize, 1,imageSize, 0), imageSize, CV_32FC1, mapX1, mapY1);
initUndistortRectifyMap(cameraMatrix2, distCoeffs2, rmat2,
getOptimalNewCameraMatrix(cameraMatrix2, distCoeffs2, imageSize, 1, imageSize, 0), imageSize, CV_32FC1, mapX2, mapY2);
// reproject points in camera 1 since its rotation has been changed
// need to find the translation between cameras based on the new camera 1 orientation
for (int i = 0; i < imagePoints1.size(); i++)
{
Mat pointsMat1 = Mat(imagePoints1[i]);
Mat pointsMat2 = Mat(imagePoints2[i]);
undistortPoints(pointsMat1, imagePoints1[i], cameraMatrix1, distCoeffs1, rmat1,getOptimalNewCameraMatrix(cameraMatrix1, distCoeffs1, imageSize, 1, imageSize, 0));
undistortPoints(pointsMat2, imagePoints2[i], cameraMatrix2, distCoeffs2, rmat2,getOptimalNewCameraMatrix(cameraMatrix2, distCoeffs2, imageSize, 1, imageSize, 0));
pointsMat1.release();
pointsMat2.release();
}
Mat temp1, temp2;
R.release();
T.release();
E.release();
F.release();
// TODO: remove this
// CalcBoardCornerPositions(s.boardSize, s.squareSize, objectPoints[0]);
// objectPoints.resize(imagePoints1.size(),objectPoints[0]);
stereoCalibrate(objectPoints, imagePoints1, imagePoints2, cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2, imageSize, R, T, E, F,
TermCriteria( CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 1000, 0.01),
CV_CALIB_FIX_INTRINSIC);
// need to alter translation matrix so
// [0] = distance in X direction (right from perspective of camera 1 is positive)
// [1] = distance in Y direction (away from camera 1 is positive)
// [2] = distance in Z direction (up is positive)
translation = T;
double temp = -translation.at<double>(0,0);
translation.at<double>(0,0) = translation.at<double>(2,0);
translation.at<double>(2,0) = temp;
cerr << "Translation reproj: " << translation << endl;
Rodrigues(R, rvec);
cerr << "Reprojected rvec: " << rvec << endl;
imagePoints1.clear();
imagePoints2.clear();
rvec.release();
rmat1.release();
rmat2.release();
R.release();
T.release();
E.release();
F.release();
rotationCalibrated = true;
}
}
imshow("Image View1", image1);
imshow("Image View2", image2);
}
}
void StereoCalib(const vector<string>& imagelist, Size boardSize, bool useCalibrated=true, bool showRectified=true)
{
if( imagelist.size() % 2 != 0 )
{
cout << "Error: the image list contains odd (non-even) number of elements\n";
return;
}
printf("board size: %d x %d", boardSize.width, boardSize.height);
bool displayCorners = true;
const int maxScale = 2;
const float squareSize = 1.f; // Set this to your actual square size
// ARRAY AND VECTOR STORAGE:
vector<vector<Point2f> > imagePoints[2];
vector<vector<Point3f> > objectPoints;
Size imageSize;
int i, j, k, nimages = (int)imagelist.size()/2;
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
vector<string> goodImageList;
for( i = j = 0; i < nimages; i++ )
{
for( k = 0; k < 2; k++ )
{
const string& filename = imagelist[i*2+k];
Mat img = imread(filename, 0);
if(img.empty())
break;
if( imageSize == Size() )
imageSize = img.size();
else if( img.size() != imageSize )
{
cout << "The image " << filename << " has the size different from the first image size. Skipping the pair\n";
break;
}
bool found = false;
vector<Point2f>& corners = imagePoints[k][j];
for( int scale = 1; scale <= maxScale; scale++ )
{
Mat timg;
if( scale == 1 )
timg = img;
else
resize(img, timg, Size(), scale, scale);
found = findChessboardCorners(timg, boardSize, corners,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_NORMALIZE_IMAGE);
if( found )
{
if( scale > 1 )
{
Mat cornersMat(corners);
cornersMat *= 1./scale;
}
break;
}
}
if( displayCorners )
{
cout << filename << endl;
Mat cimg, cimg1;
cvtColor(img, cimg, CV_GRAY2BGR);
drawChessboardCorners(cimg, boardSize, corners, found);
double sf = 640./MAX(img.rows, img.cols);
resize(cimg, cimg1, Size(), sf, sf);
imshow("corners", cimg1);
char c = (char)waitKey(500);
if( c == 27 || c == 'q' || c == 'Q' ) //Allow ESC to quit
exit(-1);
}
else
putchar('.');
if( !found )
break;
cornerSubPix(img, corners, Size(11,11), Size(-1,-1),
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS,
30, 0.01));
}
if( k == 2 )
{
goodImageList.push_back(imagelist[i*2]);
goodImageList.push_back(imagelist[i*2+1]);
j++;
}
}
cout << j << " pairs have been successfully detected.\n";
nimages = j;
if( nimages < 2 )
{
cout << "Error: too little pairs to run the calibration\n";
return;
}
imagePoints[0].resize(nimages);
imagePoints[1].resize(nimages);
objectPoints.resize(nimages);
for( i = 0; i < nimages; i++ )
{
for( j = 0; j < boardSize.height; j++ )
for( k = 0; k < boardSize.width; k++ )
objectPoints[i].push_back(Point3f(j*squareSize, k*squareSize, 0));
}
cout << "Running stereo calibration ...\n";
Mat cameraMatrix[2], distCoeffs[2];
cameraMatrix[0] = Mat::eye(3, 3, CV_64F);
cameraMatrix[1] = Mat::eye(3, 3, CV_64F);
Mat R, T, E, F;
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, E, F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),
CV_CALIB_FIX_ASPECT_RATIO +
CV_CALIB_ZERO_TANGENT_DIST +
//CV_CALIB_SAME_FOCAL_LENGTH +
CV_CALIB_RATIONAL_MODEL +
CV_CALIB_FIX_K3 + CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5);
cout << "done with RMS error=" << rms << endl;
// CALIBRATION QUALITY CHECK
// because the output fundamental matrix implicitly
// includes all the output information,
// we can check the quality of calibration using the
// epipolar geometry constraint: m2^t*F*m1=0
double err = 0;
int npoints = 0;
vector<Vec3f> lines[2];
for( i = 0; i < nimages; i++ )
{
int npt = (int)imagePoints[0][i].size();
Mat imgpt[2];
for( k = 0; k < 2; k++ )
{
imgpt[k] = Mat(imagePoints[k][i]);
undistortPoints(imgpt[k], imgpt[k], cameraMatrix[k], distCoeffs[k], Mat(), cameraMatrix[k]);
computeCorrespondEpilines(imgpt[k], k+1, F, lines[k]);
}
for( j = 0; j < npt; j++ )
{
double errij = fabs(imagePoints[0][i][j].x*lines[1][j][0] +
imagePoints[0][i][j].y*lines[1][j][1] + lines[1][j][2]) +
fabs(imagePoints[1][i][j].x*lines[0][j][0] +
imagePoints[1][i][j].y*lines[0][j][1] + lines[0][j][2]);
err += errij;
}
npoints += npt;
}
cout << "average reprojection err = " << err/npoints << endl;
// save intrinsic parameters
FileStorage fs("calib/intrinsics.yml", CV_STORAGE_WRITE);
if( fs.isOpened() )
{
fs << "M1" << cameraMatrix[0] << "D1" << distCoeffs[0] <<
"M2" << cameraMatrix[1] << "D2" << distCoeffs[1];
fs.release();
}
else
cout << "Error: can not save the intrinsic parameters\n";
Mat R1, R2, P1, P2, Q;
Rect validRoi[2];
stereoRectify(cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, R1, R2, P1, P2, Q,
CALIB_ZERO_DISPARITY, 1, imageSize, &validRoi[0], &validRoi[1]);
fs.open("calib/extrinsics.yml", CV_STORAGE_WRITE);
if( fs.isOpened() )
{
fs << "R" << R << "T" << T << "R1" << R1 << "R2" << R2 << "P1" << P1 << "P2" << P2 << "Q" << Q;
fs.release();
}
else
cout << "Error: can not save the intrinsic parameters\n";
// OpenCV can handle left-right
// or up-down camera arrangements
bool isVerticalStereo = fabs(P2.at<double>(1, 3)) > fabs(P2.at<double>(0, 3));
// COMPUTE AND DISPLAY RECTIFICATION
if( !showRectified )
return;
Mat rmap[2][2];
// IF BY CALIBRATED (BOUGUET'S METHOD)
if( useCalibrated )
{
// we already computed everything
}
// OR ELSE HARTLEY'S METHOD
else
// use intrinsic parameters of each camera, but
// compute the rectification transformation directly
// from the fundamental matrix
{
vector<Point2f> allimgpt[2];
for( k = 0; k < 2; k++ )
{
for( i = 0; i < nimages; i++ )
std::copy(imagePoints[k][i].begin(), imagePoints[k][i].end(), back_inserter(allimgpt[k]));
}
F = findFundamentalMat(Mat(allimgpt[0]), Mat(allimgpt[1]), FM_8POINT, 0, 0);
Mat H1, H2;
stereoRectifyUncalibrated(Mat(allimgpt[0]), Mat(allimgpt[1]), F, imageSize, H1, H2, 3);
R1 = cameraMatrix[0].inv()*H1*cameraMatrix[0];
R2 = cameraMatrix[1].inv()*H2*cameraMatrix[1];
P1 = cameraMatrix[0];
P2 = cameraMatrix[1];
}
//Precompute maps for cv::remap()
initUndistortRectifyMap(cameraMatrix[0], distCoeffs[0], R1, P1, imageSize, CV_16SC2, rmap[0][0], rmap[0][1]);
initUndistortRectifyMap(cameraMatrix[1], distCoeffs[1], R2, P2, imageSize, CV_16SC2, rmap[1][0], rmap[1][1]);
Mat canvas;
double sf;
int w, h;
if( !isVerticalStereo )
{
sf = 600./MAX(imageSize.width, imageSize.height);
w = cvRound(imageSize.width*sf);
h = cvRound(imageSize.height*sf);
canvas.create(h, w*2, CV_8UC3);
}
else
{
sf = 300./MAX(imageSize.width, imageSize.height);
w = cvRound(imageSize.width*sf);
h = cvRound(imageSize.height*sf);
canvas.create(h*2, w, CV_8UC3);
}
for( i = 0; i < nimages; i++ )
{
for( k = 0; k < 2; k++ )
{
Mat img = imread(goodImageList[i*2+k], 0), rimg, cimg;
remap(img, rimg, rmap[k][0], rmap[k][1], CV_INTER_LINEAR);
cvtColor(rimg, cimg, CV_GRAY2BGR);
Mat canvasPart = !isVerticalStereo ? canvas(Rect(w*k, 0, w, h)) : canvas(Rect(0, h*k, w, h));
resize(cimg, canvasPart, canvasPart.size(), 0, 0, CV_INTER_AREA);
if( useCalibrated )
{
Rect vroi(cvRound(validRoi[k].x*sf), cvRound(validRoi[k].y*sf),
cvRound(validRoi[k].width*sf), cvRound(validRoi[k].height*sf));
rectangle(canvasPart, vroi, Scalar(0,0,255), 3, 8);
}
}
if( !isVerticalStereo )
for( j = 0; j < canvas.rows; j += 16 )
line(canvas, Point(0, j), Point(canvas.cols, j), Scalar(0, 255, 0), 1, 8);
else
for( j = 0; j < canvas.cols; j += 16 )
line(canvas, Point(j, 0), Point(j, canvas.rows), Scalar(0, 255, 0), 1, 8);
imshow("rectified", canvas);
char c = (char)waitKey();
if( c == 27 || c == 'q' || c == 'Q' )
break;
}
}
