예제 #1
0
	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;
	}
예제 #4
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	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();
		}
	}
예제 #5
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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;

}
예제 #6
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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;
}
예제 #7
0
	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);
		
	}
예제 #8
0
파일: planar.cpp 프로젝트: PR2/pr2_plugs
// 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;
    }
}
예제 #9
0
        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();
}
예제 #11
0
파일: solvepnp.cpp 프로젝트: arrybn/opencv
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;
}
예제 #12
0
/// 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);
    }
}
예제 #13
0
파일: calib.cpp 프로젝트: mvernacc/RT
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;
    }
}