  We propose a method for estimating the 3D pose for the camera of a mobile
device in outdoor conditions, using only an untextured 2D model. Previous
methods compute only a relative pose using a SLAM algorithm, or require many
registered images, which are cumbersome to acquire. By contrast, our method
returns an accurate, absolute camera pose in an absolute referential using
simple 2D+height maps, which are broadly available, to refine a first estimate
of the pose provided by the device's sensors. We show how to first estimate the
camera absolute orientation from straight line segments, and then how to
estimate the translation by aligning the 2D map with a semantic segmentation of
the input image. We demonstrate the robustness and accuracy of our approach on
a challenging dataset.
