c++ - OpenCV calibrateCamera 不收敛到正确的解决方案(投影仪校准)-6ren

c++ - OpenCV calibrateCamera 不收敛到正确的解决方案(投影仪校准)

转载作者：太空狗更新时间：2023-10-29 23:04:10

我正在尝试使用 cv::calibrateCamera 来校准相机+投影仪系统。虽然它有时似乎有效，但在许多情况下，估计的解决方案似乎与正确的解决方案相去甚远。

这是一个显示问题的代码示例(包括所有数据 - 因此它相当大)

#include <opencv2/core/core.hpp>
#include <opencv2/calib3d/calib3d.hpp>

#include <iostream>
#include <vector>

cv::Mat calculateTransformation(cv::Mat translationVec, cv::Mat rotationVec) {
    cv::Mat rotationMat3x3;
    cv::Rodrigues(rotationVec, rotationMat3x3);
    cv::Mat rotationMat = cv::Mat::eye(4, 4, CV_64F);
    rotationMat3x3.copyTo(rotationMat(cv::Rect(0, 0, 3, 3)));

    cv::Mat translationMat = cv::Mat::eye(4, 4, CV_64F);
    translationVec.copyTo(translationMat(cv::Rect(3, 0, 1, 3)));

    return translationMat * rotationMat;
}

int main() {
    std::vector<cv::Point2f> image_points;
    std::vector<cv::Point3f> object_points;

    image_points.push_back(cv::Point2f(400.0f, 940.0f));
    image_points.push_back(cv::Point2f(480.0f, 940.0f));
    image_points.push_back(cv::Point2f(560.0f, 940.0f));
    image_points.push_back(cv::Point2f(640.0f, 940.0f));
    image_points.push_back(cv::Point2f(720.0f, 940.0f));
    image_points.push_back(cv::Point2f(800.0f, 940.0f));
    image_points.push_back(cv::Point2f(880.0f, 940.0f));
    image_points.push_back(cv::Point2f(960.0f, 940.0f));
    image_points.push_back(cv::Point2f(1040.0f, 940.0f));
    image_points.push_back(cv::Point2f(1120.0f, 940.0f));
    image_points.push_back(cv::Point2f(1200.0f, 940.0f));
    image_points.push_back(cv::Point2f(1280.0f, 940.0f));
    image_points.push_back(cv::Point2f(400.0f, 860.0f));
    image_points.push_back(cv::Point2f(480.0f, 860.0f));
    image_points.push_back(cv::Point2f(560.0f, 860.0f));
    image_points.push_back(cv::Point2f(640.0f, 860.0f));
    image_points.push_back(cv::Point2f(720.0f, 860.0f));
    image_points.push_back(cv::Point2f(800.0f, 860.0f));
    image_points.push_back(cv::Point2f(880.0f, 860.0f));
    image_points.push_back(cv::Point2f(960.0f, 860.0f));
    image_points.push_back(cv::Point2f(1040.0f, 860.0f));
    image_points.push_back(cv::Point2f(1120.0f, 860.0f));
    image_points.push_back(cv::Point2f(1200.0f, 860.0f));
    image_points.push_back(cv::Point2f(1280.0f, 860.0f));
    image_points.push_back(cv::Point2f(400.0f, 780.0f));
    image_points.push_back(cv::Point2f(480.0f, 780.0f));
    image_points.push_back(cv::Point2f(560.0f, 780.0f));
    image_points.push_back(cv::Point2f(640.0f, 780.0f));
    image_points.push_back(cv::Point2f(720.0f, 780.0f));
    image_points.push_back(cv::Point2f(800.0f, 780.0f));
    image_points.push_back(cv::Point2f(880.0f, 780.0f));
    image_points.push_back(cv::Point2f(960.0f, 780.0f));
    image_points.push_back(cv::Point2f(1040.0f, 780.0f));
    image_points.push_back(cv::Point2f(1120.0f, 780.0f));
    image_points.push_back(cv::Point2f(1200.0f, 780.0f));
    image_points.push_back(cv::Point2f(1280.0f, 780.0f));
    image_points.push_back(cv::Point2f(400.0f, 700.0f));
    image_points.push_back(cv::Point2f(480.0f, 700.0f));
    image_points.push_back(cv::Point2f(560.0f, 700.0f));
    image_points.push_back(cv::Point2f(640.0f, 700.0f));
    image_points.push_back(cv::Point2f(720.0f, 700.0f));
    image_points.push_back(cv::Point2f(800.0f, 700.0f));
    image_points.push_back(cv::Point2f(880.0f, 700.0f));
    image_points.push_back(cv::Point2f(960.0f, 700.0f));
    image_points.push_back(cv::Point2f(1040.0f, 700.0f));
    image_points.push_back(cv::Point2f(1120.0f, 700.0f));
    image_points.push_back(cv::Point2f(1200.0f, 700.0f));
    image_points.push_back(cv::Point2f(1280.0f, 700.0f));
    image_points.push_back(cv::Point2f(400.0f, 620.0f));
    image_points.push_back(cv::Point2f(480.0f, 620.0f));
    image_points.push_back(cv::Point2f(560.0f, 620.0f));
    image_points.push_back(cv::Point2f(640.0f, 620.0f));
    image_points.push_back(cv::Point2f(720.0f, 620.0f));
    image_points.push_back(cv::Point2f(800.0f, 620.0f));
    image_points.push_back(cv::Point2f(880.0f, 620.0f));
    image_points.push_back(cv::Point2f(960.0f, 620.0f));
    image_points.push_back(cv::Point2f(1120.0f, 620.0f));
    image_points.push_back(cv::Point2f(1040.0f, 620.0f));
    image_points.push_back(cv::Point2f(1200.0f, 620.0f));
    image_points.push_back(cv::Point2f(1280.0f, 620.0f));
    image_points.push_back(cv::Point2f(400.0f, 540.0f));
    image_points.push_back(cv::Point2f(480.0f, 540.0f));
    image_points.push_back(cv::Point2f(560.0f, 540.0f));
    image_points.push_back(cv::Point2f(640.0f, 540.0f));
    image_points.push_back(cv::Point2f(720.0f, 540.0f));
    image_points.push_back(cv::Point2f(800.0f, 540.0f));
    image_points.push_back(cv::Point2f(880.0f, 540.0f));
    image_points.push_back(cv::Point2f(1200.0f, 540.0f));
    image_points.push_back(cv::Point2f(1120.0f, 540.0f));
    image_points.push_back(cv::Point2f(480.0f, 460.0f));
    image_points.push_back(cv::Point2f(400.0f, 460.0f));
    image_points.push_back(cv::Point2f(560.0f, 460.0f));
    image_points.push_back(cv::Point2f(720.0f, 460.0f));
    image_points.push_back(cv::Point2f(640.0f, 460.0f));
    image_points.push_back(cv::Point2f(800.0f, 460.0f));
    image_points.push_back(cv::Point2f(1120.0f, 460.0f));
    image_points.push_back(cv::Point2f(880.0f, 460.0f));
    image_points.push_back(cv::Point2f(1040.0f, 460.0f));
    image_points.push_back(cv::Point2f(1280.0f, 460.0f));
    image_points.push_back(cv::Point2f(1120.0f, 380.0f));
    image_points.push_back(cv::Point2f(1280.0f, 380.0f));
    image_points.push_back(cv::Point2f(1200.0f, 380.0f));
    image_points.push_back(cv::Point2f(1040.0f, 380.0f));
    image_points.push_back(cv::Point2f(880.0f, 380.0f));
    image_points.push_back(cv::Point2f(800.0f, 380.0f));
    image_points.push_back(cv::Point2f(960.0f, 380.0f));
    image_points.push_back(cv::Point2f(640.0f, 380.0f));
    image_points.push_back(cv::Point2f(720.0f, 380.0f));
    image_points.push_back(cv::Point2f(560.0f, 380.0f));
    image_points.push_back(cv::Point2f(400.0f, 380.0f));
    image_points.push_back(cv::Point2f(480.0f, 380.0f));
    image_points.push_back(cv::Point2f(1120.0f, 300.0f));
    image_points.push_back(cv::Point2f(1040.0f, 300.0f));
    image_points.push_back(cv::Point2f(960.0f, 300.0f));
    image_points.push_back(cv::Point2f(880.0f, 300.0f));
    image_points.push_back(cv::Point2f(800.0f, 300.0f));
    image_points.push_back(cv::Point2f(720.0f, 300.0f));
    image_points.push_back(cv::Point2f(640.0f, 300.0f));
    image_points.push_back(cv::Point2f(560.0f, 300.0f));
    image_points.push_back(cv::Point2f(480.0f, 300.0f));
    image_points.push_back(cv::Point2f(400.0f, 300.0f));
    image_points.push_back(cv::Point2f(1280.0f, 220.0f));
    image_points.push_back(cv::Point2f(1200.0f, 220.0f));
    image_points.push_back(cv::Point2f(1120.0f, 220.0f));
    image_points.push_back(cv::Point2f(1040.0f, 220.0f));
    image_points.push_back(cv::Point2f(960.0f, 220.0f));
    image_points.push_back(cv::Point2f(800.0f, 220.0f));
    image_points.push_back(cv::Point2f(720.0f, 220.0f));
    image_points.push_back(cv::Point2f(640.0f, 220.0f));
    image_points.push_back(cv::Point2f(560.0f, 220.0f));
    image_points.push_back(cv::Point2f(480.0f, 220.0f));
    image_points.push_back(cv::Point2f(400.0f, 220.0f));
    image_points.push_back(cv::Point2f(1280.0f, 140.0f));
    image_points.push_back(cv::Point2f(1200.0f, 140.0f));
    image_points.push_back(cv::Point2f(1040.0f, 140.0f));
    image_points.push_back(cv::Point2f(960.0f, 140.0f));
    image_points.push_back(cv::Point2f(800.0f, 140.0f));
    image_points.push_back(cv::Point2f(720.0f, 140.0f));
    image_points.push_back(cv::Point2f(640.0f, 140.0f));
    image_points.push_back(cv::Point2f(560.0f, 140.0f));
    image_points.push_back(cv::Point2f(480.0f, 140.0f));
    image_points.push_back(cv::Point2f(400.0f, 140.0f));
    image_points.push_back(cv::Point2f(960.0f, 540.0f));
    image_points.push_back(cv::Point2f(1040.0f, 540.0f));
    image_points.push_back(cv::Point2f(960.0f, 460.0f));

    object_points.push_back(cv::Point3f(-0.0671159000000000f, -0.0530089000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0572335000000000f, -0.0531021000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0473920000000000f, -0.0531268000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0375422000000000f, -0.0531293000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0277093000000000f, -0.0532232000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0179416000000000f, -0.0532900000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00818986000000000f, -0.0533080000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00159555000000000f, -0.0533734000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0113126000000000f, -0.0534102000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0210113000000000f, -0.0534688000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0307716000000000f, -0.0535300000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0404079000000000f, -0.0535600000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0668703000000000f, -0.0429498000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0569997000000000f, -0.0430325000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0471452000000000f, -0.0430930000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0373059000000000f, -0.0431530000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0274813000000000f, -0.0432117000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0176713000000000f, -0.0432687000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00790218000000000f, -0.0433224000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00190183000000000f, -0.0433762000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0116116000000000f, -0.0434242000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0213028000000000f, -0.0434700000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0310283000000000f, -0.0435404000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0406556000000000f, -0.0436058000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0666877000000000f, -0.0329366000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0568031000000000f, -0.0329860000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0469101000000000f, -0.0330818000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0370300000000000f, -0.0331543000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0272122000000000f, -0.0332004000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0173840000000000f, -0.0332688000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00759575000000000f, -0.0333343000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00215042000000000f, -0.0334201000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0119054000000000f, -0.0334816000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0215901000000000f, -0.0335390000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0313087000000000f, -0.0336208000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0409288000000000f, -0.0336740000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0664698000000000f, -0.0228786000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0565702000000000f, -0.0229386000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0466851000000000f, -0.0230437000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0367625000000000f, -0.0230813000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0269267000000000f, -0.0231839000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0171296000000000f, -0.0232845000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00732099000000000f, -0.0232912000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00244503000000000f, -0.0234120000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0121943000000000f, -0.0235079000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0218997000000000f, -0.0235779000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0316661000000000f, -0.0236490000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0413080000000000f, -0.0237153000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0662403000000000f, -0.0127937000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0563243000000000f, -0.0128856000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0464450000000000f, -0.0129539000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0365046000000000f, -0.0130461000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0266992000000000f, -0.0131572000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0168820000000000f, -0.0132217000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00702858000000000f, -0.0133096000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00273311000000000f, -0.0134175000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0222048000000000f, -0.0135829000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0124779000000000f, -0.0135008000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0319668000000000f, -0.0136414000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0416578000000000f, -0.0137210000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0660230000000000f, -0.00272328000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0560886000000000f, -0.00280125000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0461911000000000f, -0.00292352000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0362558000000000f, -0.00302379000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0264298000000000f, -0.00309841000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0165924000000000f, -0.00321897000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00674314000000000f, -0.00331641000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0322628000000000f, -0.00369330000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0225310000000000f, -0.00360024000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0558388000000000f, 0.00733873000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0657448000000000f, 0.00744612000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0458967000000000f, 0.00723106000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0261183000000000f, 0.00701760000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0359654000000000f, 0.00710082000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0162843000000000f, 0.00688856000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0228789000000000f, 0.00646718000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00641300000000000f, 0.00678188000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0131059000000000f, 0.00657206000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0422672000000000f, 0.00628497000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0231953000000000f, 0.0165035000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0425539000000000f, 0.0162757000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0328968000000000f, 0.0163892000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0133982000000000f, 0.0166424000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00611577000000000f, 0.0168486000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0160094000000000f, 0.0169642000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00368791000000000f, 0.0167334000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0357336000000000f, 0.0171710000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0258655000000000f, 0.0170562000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0456858000000000f, 0.0173090000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0655273000000000f, 0.0175171000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0555765000000000f, 0.0174012000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0235599000000000f, 0.0266047000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0137369000000000f, 0.0267060000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00400251000000000f, 0.0268771000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.00579988000000000f, 0.0269546000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0156666000000000f, 0.0270784000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0255455000000000f, 0.0272245000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0354855000000000f, 0.0273244000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0454115000000000f, 0.0274243000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0553239000000000f, 0.0275921000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0652735000000000f, 0.0276931000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0432836000000000f, 0.0364607000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0335970000000000f, 0.0365698000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0239205000000000f, 0.0367035000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0140970000000000f, 0.0368368000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00436217000000000f, 0.0369936000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0152808000000000f, 0.0372578000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0252343000000000f, 0.0373656000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0351242000000000f, 0.0374961000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0450986000000000f, 0.0376261000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0550835000000000f, 0.0377566000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0649853000000000f, 0.0379110000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0436747000000000f, 0.0466393000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0339311000000000f, 0.0467559000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0144269000000000f, 0.0470150000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00466523000000000f, 0.0471564000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0150279000000000f, 0.0474823000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0248820000000000f, 0.0475522000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0348463000000000f, 0.0476901000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0447968000000000f, 0.0478509000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0547835000000000f, 0.0479670000000000f, 0.0f));
    object_points.push_back(cv::Point3f(-0.0647592000000000f, 0.0481078000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00301477000000000f, -0.00341146000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.0128075000000000f, -0.00350684000000000f, 0.0f));
    object_points.push_back(cv::Point3f(0.00336785000000000f, 0.00670002000000000f, 0.0f));

    std::vector<std::vector<cv::Point2f>> all_image_points;
    all_image_points.push_back(image_points);
    std::vector<std::vector<cv::Point3f>> all_object_points;
    all_object_points.push_back(object_points);

    cv::Mat camera_mat = cv::Mat::eye(3, 3, CV_64F);
    cv::Mat dist_coeffs = cv::Mat::zeros(4, 1, CV_64F);
    std::vector<cv::Mat> rvecs;
    std::vector<cv::Mat> tvecs;

    double reprojection_error = cv::calibrateCamera(all_object_points, all_image_points, cv::Size(1920, 1080), camera_mat, dist_coeffs, rvecs, tvecs);
    std::cout << "Reprojection error: " << reprojection_error << std::endl;

    cv::Mat transformation = calculateTransformation(tvecs.front(), rvecs.front());
    cv::Mat origin = cv::Mat::zeros(4, 1, CV_64F);
    origin.at<double>(3, 0) = 1.0;
    std::cout << "distance to board: " << cv::norm(transformation * origin) << std::endl;

    return 0;
}

目标点以米为单位
到板的距离应约为 0.64 米(估计为 1.7 米)
径向失真参数 k2 的值高于 200，这有点奇怪
我已使用 matlab 可视化我的输入数据以验证对应关系是否正确
我知道通过多次捕获可以获得更强大的解决方案，但发布的数据似乎对解决方案的影响相当大。进行了两次捕获，产生了一个看起来正确的解决方案，添加了另一个导致错误解决方案的捕获(发布的数据)。
我猜数据比常规校准数据噪音大一些，因为我无法直接捕获数据(这是投影仪校准)，但需要使用检测投影图案的相机

如果有人想使用 matlab 可视化数据:我已经简单地使用了

plot3([image_points(1,:);object_points(1,:) * 10000], [image_points(2,:);object_points(2,:) * -10000], [zeros(1, 125); ones(1, 125)], 'b-')

因此，对象和图像点之间的每个对应对应一行。

如果需要更多信息，请发表评论。

最佳答案

我的提议是在相机校准过程中使用不同的非共面装备(表面)。 opencv 使用的算法肯定需要至少两个不同的 View 才能执行良好的校准。如果可能，提供几个不同角度的 View (2 个只是起点，最好是 10 个)。我现在不是 100% 确定，但我认为非平面要求是 sine qua non 条件，即你不能用共面 View 获得好的结果(因为实际上它们只是根据比例不同因此在某些词中我们可以说它们在投影几何方面是同构的)。

还有一个关于投影误差的评论——在测试案例中大约是 0.65，这似乎是准确的……但这是棘手的部分——因为我们只使用一个装备来校准相机，所以根据定义，当 opencv 重新投影回点时，它只有一个表面可以重新投影到。换言之，标定误差很小且大于零，只是因为存在给定点投影的噪声。

关于c++ - OpenCV calibrateCamera 不收敛到正确的解决方案(投影仪校准)，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/23568696/

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c++ - OpenCV calibrateCamera 不收敛到正确的解决方案(投影仪校准)