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Merge branch 4.x

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This commit is contained in:
Alexander Alekhin
2023-01-28 13:08:29 +00:00
parent 8329c09ba8 cd44aa0bb1
commit f33598f55e
91 changed files with 1245 additions and 303 deletions
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modules/calib/src/calibration.cpp
+13 -10
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@@ -404,6 +404,12 @@ static double calibrateCameraInternal( const Mat& objectPoints,
mask[nparams - 1] = 0;
}
int nparams_nz = countNonZero(mask);
if (nparams_nz >= 2 * total)
CV_Error_(Error::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(int i = 0, pos = 0; i < nimages; i++ )
{
@@ -572,26 +578,23 @@ static double calibrateCameraInternal( const Mat& objectPoints,
if (!stdDevs.empty())
{
int nparams_nz = countNonZero(mask);
JtJN.create(nparams_nz, nparams_nz, CV_64F);
subMatrix(JtJ, JtJN, mask, mask);
completeSymm(JtJN, false);
//TODO: try DECOMP_CHOLESKY maybe?
cv::invert(JtJN, JtJinv, DECOMP_EIG);
// 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
double sigma2 = norm(allErrors, NORM_L2SQR) / (2 * total - nparams_nz);
int j = 0;
for ( int s = 0; s < nparams; s++ )
{
stdDevs.at<double>(s) = mask[s] ? std::sqrt(JtJinv.at<double>(j, j) * sigma2) : 0.0;
if( mask[s] )
{
stdDevs.at<double>(s) = std::sqrt(JtJinv.at<double>(j,j) * sigma2);
j++;
}
else
stdDevs.at<double>(s) = 0.;
}
}
// 4. store the results