From 5fee983ff102bda87833af53c10ba7e972eca583 Mon Sep 17 00:00:00 2001
From: John Lambert <johnlambert@gatech.edu>
Date: Wed, 21 Jul 2021 10:04:05 -0600
Subject: [PATCH] use upper 3x3 sub-block of covariance matrix for converting
 BetweenFactor to BinaryMeasurement, and use Isotropic in ShonanAveraging2

---
 gtsam/sfm/ShonanAveraging.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/gtsam/sfm/ShonanAveraging.cpp b/gtsam/sfm/ShonanAveraging.cpp
index 76fd1bfc70..a5b6a8d9ac 100644
--- a/gtsam/sfm/ShonanAveraging.cpp
+++ b/gtsam/sfm/ShonanAveraging.cpp
@@ -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);
 }