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

Joint Facade Registration and Segmentation for Urban Localization