如何使用 openCV 正确校准带有广角镜头的相机?

the matrices and rms being output by the calibration:

K:[263.7291703200009, 0, 395.1618975493187;
 0, 144.3800397321767, 188.9308218101271;
 0, 0, 1]

D:[0, 0, 0, 0]

rms: 9.27628

我的代码:

#include <opencv2/opencv.hpp>
#include "opencv2/core.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/ccalib/omnidir.hpp"

using namespace std;
using namespace cv;

vector<vector<Point2d> > points2D;
vector<vector<Point3d> > objectPoints;

Mat src;

//so that I don't have to select them manually every time
void initializePoints2D()
{
    points2D[0].push_back(Point2d(234, 128));
    points2D[0].push_back(Point2d(300, 124));
    points2D[0].push_back(Point2d(381, 126));
    points2D[0].push_back(Point2d(460, 127));
    points2D[0].push_back(Point2d(529, 137));
    points2D[0].push_back(Point2d(207, 147));
    points2D[0].push_back(Point2d(280, 147));
    points2D[0].push_back(Point2d(379, 146));
    points2D[0].push_back(Point2d(478, 153));
    points2D[0].push_back(Point2d(551, 165));
    points2D[0].push_back(Point2d(175, 180));
    points2D[0].push_back(Point2d(254, 182));
    points2D[0].push_back(Point2d(377, 185));
    points2D[0].push_back(Point2d(502, 191));
    points2D[0].push_back(Point2d(586, 191));
    points2D[0].push_back(Point2d(136, 223));
    points2D[0].push_back(Point2d(216, 239));
    points2D[0].push_back(Point2d(373, 253));
    points2D[0].push_back(Point2d(534, 248));
    points2D[0].push_back(Point2d(624, 239));
    points2D[0].push_back(Point2d(97, 281));
    points2D[0].push_back(Point2d(175, 322));
    points2D[0].push_back(Point2d(370, 371));
    points2D[0].push_back(Point2d(578, 339));
    points2D[0].push_back(Point2d(662, 298));


    for(int j=0; j<25;j++)
    {   
        circle(src, points2D[0].at(j), 5, Scalar(0, 0, 255), 1, 8, 0);
    }

    imshow("src with circles", src);
    waitKey(0);
}

int main(int argc, char** argv)
{
    Mat srcSaved;

    src = imread("images/frontCar.png");
    resize(src, src, Size(), 0.5, 0.5);
    src.copyTo(srcSaved);

    vector<Point3d> objectPointsRow;
    vector<Point2d> points2DRow;
    objectPoints.push_back(objectPointsRow);
    points2D.push_back(points2DRow);

    for(int i=0; i<5;i++)
    {

        for(int j=0; j<5;j++)
        {
            objectPoints[0].push_back(Point3d(5*j,5*i,1));        
        }
    }

    initializePoints2D();
    cv::Matx33d K;
    cv::Vec4d D;
    std::vector<cv::Vec3d> rvec;
    std::vector<cv::Vec3d> tvec;


    int flag = 0;
    flag |= cv::fisheye::CALIB_RECOMPUTE_EXTRINSIC;
    flag |= cv::fisheye::CALIB_CHECK_COND;
    flag |= cv::fisheye::CALIB_FIX_SKEW; 
    flag |= cv::fisheye::CALIB_FIX_K1; 
    flag |= cv::fisheye::CALIB_FIX_K2; 
    flag |= cv::fisheye::CALIB_FIX_K3; 
    flag |= cv::fisheye::CALIB_FIX_K4; 


    double rms =cv::fisheye::calibrate(
 objectPoints, points2D, src.size(), 
 K, D, rvec, tvec, flag, cv::TermCriteria(3, 20, 1e-6)     
 );

    Mat output;
    cerr<<"K:"<<K<<endl;
    cerr<<"D:"<<D<<endl;
    cv::fisheye::undistortImage(srcSaved, output, K, D);
    cerr<<"rms: "<<rms<<endl;
    imshow("output", output);
    waitKey(0);

    cerr<<"image .size: "<<srcSaved.size()<<endl;

}

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