Approaches to Large-Scale Urban Modeling
IEEE Computer Graphics and Applications
3D Building Detection and Modeling from Aerial LIDAR Data
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Modeling and Representations of Large-Scale 3D Scenes
International Journal of Computer Vision
Fusion of Feature- and Area-Based Information for Urban Buildings Modeling from Aerial Imagery
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Random Exploration of the Procedural Space for Single-View 3D Modeling of Buildings
International Journal of Computer Vision
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In this paper, we introduce a variational framework towards automatic 3D building reconstruction from optical and Lidar data. Multiple 3D competing building priors are considered under a recognition-driven way. These models, under a certain hierarchical representation, describe the space of solutions and under a fruitful synergy with an inferential procedure recover the observed scene's geometry. Our formulation allows the cue with the higher spatial resolution to constrain properly the boundaries detection procedure ensuring, in this way, optimal results in terms of accuracy. Such an integrated approach is defined in a variational context, solves segmentation in both spaces, addresses fusion in a natural manner and allows multiple competing priors to determine the pose and 3D geometry from the observed data. Very promising experimental results demonstrate the potentials of our approach.