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Reconstructing fine facade geometry from MMS lidar data remains a challenge: In addition to being inherently sparse, the point cloud\udprovided by a single street point of view is necessarily incomplete. We propose a simple framework to estimate the facade surface\udwith a deformable 2.5d grid. Computations are performed in a "sensor-oriented" coordinate system that maximizes consistency with\udthe data. the algorithm allows to retrieve the facade geometry without priori knowledge. It can thus be automatically applied to a large\udamount of data in spite of the variability of encountered architectural forms. The 2.5d image structure of the output makes it compatible\udwith storage and real-time constraints of immersive navigation

Facade Reconstruction with Generalized 2.5d Grids