Issue No. 01 - January (2010 vol. 32)
Florent Lafarge , Ariana Research Group, INRIA and Matis Laboratory, French Mapping Agency, Sophia Antipolis
Xavier Descombes , Ariana Research Group, INRIA, Sophia Antipolis
Josiane Zerubia , Ariana Research Group, INRIA, Sophia Antipolis
Marc Pierrot-Deseilligny , French Mapping Agency (IGN), Saint-Mandé
We present a new approach for building reconstruction from a single Digital Surface Model (DSM). It treats buildings as an assemblage of simple urban structures extracted from a library of 3D parametric blocks (like a LEGO set). First, the 2D-supports of the urban structures are extracted either interactively or automatically. Then, 3D-blocks are placed on the 2D-supports using a Gibbs model which controls both the block assemblage and the fitting to data. A Bayesian decision finds the optimal configuration of 3D--blocks using a Markov Chain Monte Carlo sampler associated with original proposition kernels. This method has been validated on multiple data set in a wide-resolution interval such as 0.7 m satellite and 0.1 m aerial DSMs, and provides 3D representations on complex buildings and dense urban areas with various levels of detail.
3D reconstruction, urban area, digital surface model, stochastic models, Monte Carlo simulations.
M. Pierrot-Deseilligny, J. Zerubia, F. Lafarge and X. Descombes, "Structural Approach for Building Reconstruction from a Single DSM," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 32, no. , pp. 135-147, 2008.