1 files changed, 2 insertions, 14 deletions
diff --git a/extern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc b/extern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc
index 246828a644f..14030da6315 100644
--- a/extern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc
+++ b/extern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc
@@ -68,20 +68,8 @@ bool EuclideanReconstructTwoFrames(const vector<Marker> &markers,
   NormalizedEightPointSolver(x1, x2, &F);
 
   // The F matrix should be an E matrix, but squash it just to be sure.
-  Eigen::JacobiSVD<Mat3> svd(F, Eigen::ComputeFullU | Eigen::ComputeFullV);
-
-  // See Hartley & Zisserman page 294, result 11.1, which shows how to get the
-  // closest essential matrix to a matrix that is "almost" an essential matrix.
-  double a = svd.singularValues()(0);
-  double b = svd.singularValues()(1);
-  double s = (a + b) / 2.0;
-  LG << "Initial reconstruction's rotation is non-euclidean by "
-     << (((a - b) / std::max(a, b)) * 100) << "%; singular values:"
-     << svd.singularValues().transpose();
-
-  Vec3 diag;
-  diag << s, s, 0;
-  Mat3 E = svd.matrixU() * diag.asDiagonal() * svd.matrixV().transpose();
+  Mat3 E;
+  FundamentalToEssential(F, &E);
 
   // Recover motion between the two images. Since this function assumes a
   // calibrated camera, use the identity for K.