Stereo Matching Strategy for 3-D Urban Modeling (original) (raw)

Abstract

This paper proposes an effective matching strategy to reconstruct 3-D urban models in densely built-up areas. Proposed scheme includes two main steps: feature-based image matching using building recognition technique and 3-D building reconstruction using the refined Rational Function Coefficients (RFCs). Especially, our approach is focused on improving the matching efficiency in complex urban scenes. For this purpose, we first performed automatic building recognition between stereo images, and then we endowed all points of building edges with identifiers using edge tracing method. Each identifier plays an important role in reducing search space for image matching within points of same building. A standard IKONOS stereo product was used to evaluate the proposed algorithms. It turned out that the proposed method could automatically determine the initial position and could dramatically reduce search space for point matching. Also, it was demonstrated that the updated RFCs could provide high-quality 3-D urban models.

Preview

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Roux, M., Mckeown, D.M.: Feature matching for building extraction from multiple view. In: Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 331–339 (1994)
    Google Scholar
  2. Collins, R.T., Hanson, A.R., Riseman, M.R., Schultz, H.: Automatic extraction of buildings and terrain from aerial images. In: Automatic extraction of man-made objects from aerial images, pp. 169–178. Birkhauser Verlag, Basel (1995)
    Google Scholar
  3. Bignone, F., Henricsson, O., Fua, P., Stricker, M.: Automatic extraction of generic house roofs from high-resolution aerial imagery. In: Computer Vision–ECCV 1996, vol. 1, pp. 85-96 (1996)
    Google Scholar
  4. Fischer, A., Kolbe, T.H., Lang, F., Cremers, A.B., Förstner, W., Plümer, L., Steinhage, V.: Extraction buildings from aerial images using hierarchical aggregation in 2D and 3D. Computer Vision and Image Understanding 72(2), 185–203 (1998)
    Article Google Scholar
  5. Sohn, H.G., Park, C.H., Heo, J.: 3-D building reconstruction using IKONOS multispectral stereo images. LNCS (LNAI), vol. 3863, pp. 62–68. Springer, Heidelberg (2005)
    Google Scholar
  6. Kunii, Y., Chikatsu, H.: Efficient line matching by image sequential analysis for urban area modeling. In: ISPRS XXth Congress-Youth Forum, pp. 211–214 (2004)
    Google Scholar
  7. Nakagawa, M., Shibasaki, R., Kagawa, Y.: Fusing stereo linear CCD image and laser range data for building 3D urban model. In: ISPRS Commission IV Workshop, WG IV/7 (2002)
    Google Scholar
  8. Sohn, H.G., Park, C.H., Chang, H.: Rational function model-based image matching for digital elevation models. The Photogrammetric Record 20(112), 366–383 (2005)
    Article Google Scholar
  9. Heipke, C.: Overview of image matching techniques. In: OEEPE-Workshop on the application of digital photogrammetric workstations, vol. 33, pp. 173–189
    Google Scholar
  10. Huttenlocher, D.P., Klanderman, G.A., Rucklidge, W.J.: Comparing images using the hausdorff distance. IEEE Transaction on Pattern Analysis and Machine Intelligence 15(9), 850–863 (1993)
    Article Google Scholar
  11. Grodecki, J., Dial, G.: IKONOS geometric accuracy. In: Joint Workshop of ISPRS Working group I/2, I/5 and IV/7 on High Resolution Mapping from space (2001)
    Google Scholar
  12. Fraser, C.S., Hanley, H.B.: Bias compensation in rational functions for IKONOS satellite imagery. Photogrammetric Engineering & Remote Sensing 69(1), 53–57 (2003)
    Google Scholar

Download references

Author information

Authors and Affiliations

  1. School of Civil and Env. Eng., Yonsei University, Korea
    Choung-Hwan Park, Hong-Gyoo Sohn & Yeong-Sun Song

Authors

  1. Choung-Hwan Park
  2. Hong-Gyoo Sohn
  3. Yeong-Sun Song

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada
    Marina L. Gavrilova
  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy
    Osvaldo Gervasi
  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA
    Vipin Kumar
  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK
    C. J. Kenneth Tan
  5. Clayton School of IT, Monash University, 3800, Clayton, Australia
    David Taniar
  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy
    Antonio Laganá
  7. School of Computing, Soongsil University, Seoul, Korea
    Youngsong Mun
  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea
    Hyunseung Choo

Rights and permissions

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Park, CH., Sohn, HG., Song, YS. (2006). Stereo Matching Strategy for 3-D Urban Modeling. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751588\_110

Download citation

Keywords

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.

Publish with us