An Automatic 3D City Model : A Bayesian Approach Using Satellite Images

We propose a parametric model for automatic 3D reconstruction of urban areas from high resolution satellite data. An automatic building extraction method based on marked point processes is used to provide rectangular building footprints. Based on a parametric model with rectangular ground footprint, the proposed method is developed using a Bayesian approach : we search for the best configuration of parametric models with respect to both a priori knowledge of models and their interactions, and a likelihood which fits models to the DEM. A simulated annealing is used to find the configuration which maximizes the a posteriori density of the Bayesian expression