I have the following function, which is used in combination with ceres::Jet<> as scalar: template < class Derived1, class Derived2 > inline Eigen::Matrix<typename Eigen::MatrixBase<Derived1>::Scalar, 2, 1> reproject( const Eigen::MatrixBase<Derived1>& pt, const Eigen::MatrixBase<Derived2>& W ) { return (W * pt.homogeneous()).hnormalized(); } If I don't call .eval() before .hnormalized() this results in the following compilation error: /usr/include/eigen3/Eigen/src/Core/DenseCoeffsBase.h:137:14: error: no viable conversion from 'const Eigen::ReturnByValue<Eigen::internal::homogeneous_left_product_impl<Eigen::Homogeneous<Eigen::Matrix<double, 2, 1, 0, 2, 1>, 0>, Eigen::Matrix<double, 3, 3, 0, 3, 3> > >::YOU_ARE_TRYING_TO_ACCESS_A_SINGLE_COEFFICIENT_IN_A_SPECIAL_EXPRESSION_WHERE_THAT_IS_NOT_ALLOWED_BECAUSE_THAT_WOULD_BE_INEFFICIENT' to 'const double' return derived().coeff(index); ^~~~~~~~~~~~~~~~~~~~~~ /usr/include/eigen3/Eigen/src/Geometry/Homogeneous.h:163:40: note: in instantiation of member function 'Eigen::DenseCoeffsBase<Eigen::ReturnByValue<Eigen::internal::homogeneous_left_product_impl<Eigen::Homogeneous<Eigen::Matrix<double, 2, 1, 0, 2, 1>, 0>, Eigen::Matrix<double, 3, 3, 0, 3, 3> > >, 0>::coeff' requested here ColsAtCompileTime==1?1:size()-1) / coeff(size()-1); I'm using Clang 3.6 and Eigen 3.2.4.

By the way, this happens when using double as scalar as well.

The cleanest/most efficient workaround would be to store W as a Transform (and omit the homogeneous() and hnormalized() calls). But I agree that your code should compile.

I don't see how storing W in a Transform can be more efficient. Wouldn't that still require to call .homogeneous() and .hnormalized(), would it?

(In reply to Sergiu Dotenco from comment #3) > I don't see how storing W in a Transform can be more efficient. Wouldn't > that still require to call .homogeneous() and .hnormalized(), would it? I admit that I did not check the code. I wrongfully assumed, Transform * vector automatically normalizes when assigning to a vector of size dim (and not dim+1).

Indeed, hnormalized should perform the call to eval for you. In Eigen 3.3, evaluators should refactor this expression to: (W.leftCols<2>() * pt + W.col(2)).hnormalized() and, support for: W * lazyProduct( pt.homogeneous() ) has also to be added.

Actually, this is already working fine in the devel branch. The following changeset add support for lazyProduct: https://bitbucket.org/eigen/eigen/commits/57baa6174354/ Changeset: 57baa6174354 User: ggael Date: 2015-06-08 13:43:41+00:00 Summary: Bug 997: add missing evaluators for m.lazyProduct(v.homogeneous()) Backporting to 3.2 is impossible, so I vote for wontfix for 3.2 and fixed for the devel branch.

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