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Estimating 3D Polyhedral Building Models by Registering Aerial Images

  • Fadi Dornaika
  • Karim Hammoudi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6475)

Abstract

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.

Keywords

Digital Elevation Model Aerial Image Polyhedral Model Master Image Building Footprint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Fadi Dornaika
    • 1
    • 2
  • Karim Hammoudi
    • 3
  1. 1.University of the Basque CountrySan SebastianSpain
  2. 2.IKERBASQUE, Basque Foundation for ScienceBilbaoSpain
  3. 3.Institut Géographique NationalUniversité Paris-EstParisFrance

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