Large-Scale Building Reconstruction Through Information Fusion and 3-D Priors

Abstract : In this paper, a novel variational framework is introduced toward automatic 3-D building reconstruction from remote-sensing data. We consider a subset of building models that involve the footprint, their elevation, and the roof type. 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. Such an integrated approach is defined in a variational context, solves segmentation both in optical images and digital elevation maps, and allows multiple competing priors to determine their pose and 3-D geometry from the observed data. The very promising experimental results and the performed quantitative evaluation demonstrate the potentials of our approach.
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IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2010, 48 (5), pp.2283-2296. 〈10.1109/TGRS.2009.2039220〉
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Soumis le : vendredi 30 août 2013 - 14:12:30
Dernière modification le : jeudi 7 février 2019 - 17:29:17

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Konstantinos Karantzalos, Nikos Paragios. Large-Scale Building Reconstruction Through Information Fusion and 3-D Priors. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2010, 48 (5), pp.2283-2296. 〈10.1109/TGRS.2009.2039220〉. 〈hal-00856071〉

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