  This paper presents an efficient approach for solving jointly facade
registration and semantic segmentation. Progress in facade detection and
recognition enable good initialization for the registration of a reference
facade to a newly acquired target image. We propose here to rely on semantic
segmentation to improve the accuracy of that initial registration.
Simultaneously we aim to improve the quality of the semantic segmentation
through the registration. These two problems are jointly solved in a
Expectation-Maximization framework. We especially introduce a bayesian model
that use prior semantic segmentation as well as geometric structure of the
facade reference modeled by $L_p$ Gaussian Mixtures. We show the advantages of
our method in term of robustness to clutter and change of illumination on urban
images from various database.
