A 3-Dimensional Multi-View Based Strategy for Remotely Sensed Image Interpretation*

  • Theo Moons
  • David Frère
  • Luc Van Gool
Conference paper


The aim of this paper is to assess the feasibility of extracting 3- dimensional information about man-made objects from very high resolution satellite imagery. To this end, a 3-dimensional, multi-view based paradigm is proposed. The underlying philosophy is to generate from the images reliable geometric 3D features, exploiting the multi-view geometric constraints for blunder correction. Scene analysis is performed by reasoning in 3D world space and verified in the images by means of a hypothesis generation and verification procedure in which the decisions are taken on the basis of a multi-view consensus. As an example of such an approach, a method for automatic modelling and 3D reconstruction of buildings is discussed and the effects of the resolution of the new generation satellite data on the performance of the algorithm and the metric accuracy of the final reconstruction is investigated.


Line Segment Aerial Image Roof Structure Dense Urban Area Final Reconstruction 
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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  1. 1.
    F. Bignone, O. Henricsson, P. Fua, M. Strieker, “Automatic extraction of generic house roofs from high resolution aerial imagery”, B. Buxton and R. Cipolla (eds.), Computer Vision – ECCV’96, LNCS 1064, pp. 85–96, Springer-Verlag, Berlin, 1996.Google Scholar
  2. 2.
    A. Fischer, T.H. Kolbe and F. Lang, “Integration of 2D and 3D reasoning for building reconstruction using a generic hierarchical model”, In Semantic Modelling for the Acquisition of Topographic Information from Images and Maps, W. Forstner and L. Plümer (eds.), pp. 159–180, Birkhauser-Verlag, Basel, 1997.Google Scholar
  3. 3.
    A. Grim, O. Kübler and P. Agouris, Automatic Extraction of Man-Made Objects from Aerial and Space Images, Birkhauser-Verlag, Basel, 1995.Google Scholar
  4. 4.
    A. Grün, E.P. Baltsavias and O. Henricsson, Automatic Extraction of Man- Made Objects from Aerial and Space Images (II), Birkhauser-Verlag, Basel, 1997.CrossRefGoogle Scholar
  5. 5.
    J. Mc Glone and J. Shuffelt, “Projective and object space geometry for monocular building extraction”, in Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR ;94), Seattle, WA, pp. 54-61, June 1994.Google Scholar
  6. 6.
    R. Mohan and R. Nevatia, “Perceptual organisation for scene segmentation and description”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 6, pp. 616–635, 1992.CrossRefGoogle Scholar
  7. 7.
    T. Moons, D. Frère, J. Vandekerckhove, and L. VanGool, “Automatic Modelling and 3D Reconstruction of Urban House Roofs from High Resolution Aerial Imagery”, inComputer Vision – ECCV’98, H. Burkhardt and B. Neumann (eds.), LNCS 1406, pp. I140–I425, Springer-Verlag, Berlin, 1998.Google Scholar
  8. 8.
    R. Nevatia, C. Lin and A. Huertas, “A system for building detection from aerial images”, in Automatic Extraction of Man-Made Objects from Aerial and Space Images (II), A. Griin, E.P. Baltsavias and O. Henricsson, (eds.), Birkhauser-Verlag, Basel, pp. 77–86, 1997.CrossRefGoogle Scholar
  9. 9.
    M. Roux and D. McKeown, “Feature matching for building extraction from multiple views”, in Proceedings ARPA Image Understanding Workshop (IUW’94), Monterey, CA, pp. 331–349, 1994.Google Scholar
  10. 10.
    M. Roux and H. Maitre, “Three-dimensional description of dense urban areas using maps and aerial images”,in Automatic Extraction of Man-Made Objects from Aerial and Space Images (II), A. Griin, E.P. Baltsavias and O. Henricsson, (eds.), Birkhauser-Verlag, Basel, pp. 311–322, 1997.CrossRefGoogle Scholar
  11. 11.
    T. Tuytelaars, L. VanGool, M. Proesmans, and T. Moons, “A cascaded Hough transform as an aid in aerial image interpretation”, in Proceedings International Conference on Computer Vision (ICCV’98), Bombay, India, pp. 67–72, January 1998.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1999

Authors and Affiliations

  • Theo Moons
    • 1
  • David Frère
    • 1
  • Luc Van Gool
    • 1
  1. 1.Katholieke Universiteit Leuven, ESAT - PSI, KardHeverleeBelgium

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