Estimating 3D Polyhedral Building Models by Registering Aerial Images
We describe a model driven approach for extracting simple 3D polyhedral building models from aerial images. The novelty of the approach lies in the use of featureless and direct optimization based on image rawbrightness. The 3D polyhedral model is estimated by optimizing a criterion that combines a global dissimilarity measure and a gradient score over several aerial images. The proposed approach gives more accurate 3D reconstruction than feature-based approaches since it does not involve intermediate noisy data (e.g., the 3D points of a noisy Digital Elevation Model). We provide experiments and evaluations of performance. Experimental results show the feasibility and robustness of the proposed approach.
KeywordsDigital Elevation Model Aerial Image Polyhedral Model Master Image Building Footprint
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