We introduce a spatially dense variational approach to estimate the calibration of multiple cameras in the context of 3D reconstruction. We propose a relaxation scheme which allows to transform the original photometric error into a geometric one, thereby decoupling the problems of dense matching and camera calibration. In both quantitative and qualitative experiments, we demonstrate that the proposed decoupling scheme allows for robust and accurate estimation of camera parameters. In particular, the presented dense camera calibration formulation leads to substantial improvements both in the reconstructed 3D geometry and in the super-resolution texture estimation.