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Backport to 3.4: fixing how stdDev in calibration is calculated #23025

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merged 2 commits into from Jan 23, 2023
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25 changes: 14 additions & 11 deletions modules/calib3d/src/calibration.cpp
Expand Up @@ -1549,6 +1549,12 @@ static double cvCalibrateCamera2Internal( const CvMat* objectPoints,
}
}

Mat mask = cvarrToMat(solver.mask);
int nparams_nz = countNonZero(mask);
if (nparams_nz >= 2 * total)
CV_Error_(CV_StsBadArg,
("There should be less vars to optimize (having %d) than the number of residuals (%d = 2 per point)", nparams_nz, 2 * total));

// 2. initialize extrinsic parameters
for( i = 0, pos = 0; i < nimages; i++, pos += ni )
{
Expand Down Expand Up @@ -1651,27 +1657,24 @@ static double cvCalibrateCamera2Internal( const CvMat* objectPoints,
{
if( stdDevs )
{
Mat mask = cvarrToMat(solver.mask);
int nparams_nz = countNonZero(mask);
Mat JtJinv, JtJN;
JtJN.create(nparams_nz, nparams_nz, CV_64F);
subMatrix(cvarrToMat(_JtJ), JtJN, mask, mask);
completeSymm(JtJN, false);
cv::invert(JtJN, JtJinv, DECOMP_SVD);
//sigma2 is deviation of the noise
//see any papers about variance of the least squares estimator for
//detailed description of the variance estimation methods
double sigma2 = norm(allErrors, NORM_L2SQR) / (total - nparams_nz);
// an explanation of that denominator correction can be found here:
// R. Hartley, A. Zisserman, Multiple View Geometry in Computer Vision, 2004, section 5.1.3, page 134
// see the discussion for more details: https://github.com/opencv/opencv/pull/22992
int nErrors = 2 * total - nparams_nz;
double sigma2 = norm(allErrors, NORM_L2SQR) / nErrors;
Mat stdDevsM = cvarrToMat(stdDevs);
int j = 0;
for ( int s = 0; s < nparams; s++ )
{
stdDevsM.at<double>(s) = mask.data[s] ? std::sqrt(JtJinv.at<double>(j,j) * sigma2) : 0.0;
if( mask.data[s] )
{
stdDevsM.at<double>(s) = std::sqrt(JtJinv.at<double>(j,j) * sigma2);
j++;
}
else
stdDevsM.at<double>(s) = 0.;
}
}
break;
}
Expand Down