quick reimplementation of SVD from the numeral recipes book:

this is still not Eigen style code but at least it works for
n>m and it is more accurate than the JAMA based version. (I needed
it now, this is why I did that)

1 files changed, 3 insertions, 2 deletions

diff --git a/Eigen/src/Geometry/Quaternion.h b/Eigen/src/Geometry/Quaternion.h
index a76ccbdaf..8d1bbf9d2 100644
--- a/Eigen/src/Geometry/Quaternion.h
+++ b/Eigen/src/Geometry/Quaternion.h
@@ -371,13 +371,14 @@ inline Quaternion<Scalar>& Quaternion<Scalar>::setFromTwoVectors(const MatrixBas
   if (ei_isApprox(c,Scalar(-1)))
   {
     c = std::max<Scalar>(c,-1);
-
-    SVD<Matrix<Scalar,3,3> > svd(v0 * v0.transpose() + v1 * v1.transpose());
+    Matrix<Scalar,2,3> m; m << v0.transpose(), v1.transpose();
+    SVD<Matrix<Scalar,2,3> > svd(m);
     Vector3 axis = svd.matrixV().col(2);
     
     Scalar w2 = (Scalar(1)+c)*Scalar(0.5);
     this->w() = ei_sqrt(w2);
     this->vec() = axis * ei_sqrt(Scalar(1) - w2);
+    
     return *this;
   }