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use upper 3x3 sub-block of covariance matrix for converting BetweenFactor to BinaryMeasurement, and use Isotropic in ShonanAveraging2

release/4.3a0
John Lambert 2021-07-21 10:04:05 -06:00 committed by GitHub
parent 838e74dbc8
commit 5fee983ff1
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1 changed files with 2 additions and 2 deletions
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4
gtsam/sfm/ShonanAveraging.cpp
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@ -955,7 +955,7 @@ static BinaryMeasurement<Rot2> convertPose2ToBinaryMeasurementRot2(
"parseMeasurements<Rot2> can only convert Pose2 measurements "
"with Gaussian noise models.");
const Matrix3 M = gaussian->covariance();
auto model = noiseModel::Gaussian::Covariance(M.block<1, 1>(2, 2));
auto model = noiseModel::Isotropic::Variance(1, M(2, 2));
return BinaryMeasurement<Rot2>(f->key1(), f->key2(), f->measured().rotation(),
model);
}
@ -1001,7 +1001,7 @@ static BinaryMeasurement<Rot3> convert(
"parseMeasurements<Rot3> can only convert Pose3 measurements "
"with Gaussian noise models.");
const Matrix6 M = gaussian->covariance();
auto model = noiseModel::Gaussian::Covariance(M.block<3, 3>(3, 3));
auto model = noiseModel::Gaussian::Covariance(M.block<3, 3>(0, 0));
return BinaryMeasurement<Rot3>(f->key1(), f->key2(), f->measured().rotation(),
model);
}