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; } }