© 1995

Automatic Extraction of Man-Made Objects from Aerial and Space Images

  • Armin Gruen
  • Olaf Kuebler
  • Peggy Agouris
Conference proceedings

Part of the Monte Verità book series (MV)

Table of contents

  1. Front Matter
    Pages i-viii
  2. General Strategies

    1. Front Matter
      Pages 1-1
    2. Andres Huertas, Mathias Bejanin, Ramakant Nevatia
      Pages 33-42
    3. Walter Mueller, James Olson
      Pages 43-52
    4. Uwe Stilla, Eckart Michaelsen, Karl Lütjen
      Pages 53-62
    5. Vittala K. Shettigara, Siegfried G. Kempinger, Robert Aitchison
      Pages 63-72
    6. John C. Trinder, Haihong Li
      Pages 95-104
    7. W. Neuenschwander, P. Fua, G. Székely, O. Kübler
      Pages 105-114
  3. Building Extraction

    1. Front Matter
      Pages 115-115
    2. Chungan Lin, Andres Huertas, Ramakant Nevatia
      Pages 125-134
    3. M. Berthod, L. Gabet, G. Giraudon, J. L. Lotti
      Pages 135-144
    4. Olivier Faugeras, Stéphane Laveau, Luc Robert, Gabriella Csurka, Cyril Zeller
      Pages 145-168
    5. Robert T. Collins, Allen R. Hanson, Edward M. Riseman, Howard Schultz
      Pages 169-178

About these proceedings


Advancements in digital sensor technology, digital image analysis techniques, as well as computer software and hardware have brought together the fields of computer vision and photogrammetry, which are now converging towards sharing, to a great extent, objectives and algorithms. The potential for mutual benefits by the close collaboration and interaction of these two disciplines is great, as photogrammetric know-how can be aided by the most recent image analysis developments in computer vision, while modern quantitative photogrammetric approaches can support computer vision activities. Devising methodologies for automating the extraction of man-made objects (e.g. buildings, roads) from digital aerial or satellite imagery is an application where this cooperation and mutual support is already reaping benefits. The valuable spatial information collected using these interdisciplinary techniques is of improved qualitative and quantitative accuracy. This book offers a comprehensive selection of high-quality and in-depth contributions from world-wide leading research institutions, treating theoretical as well as implementational issues, and representing the state-of-the-art on this subject among the photogrammetric and computer vision communities.


Geoinformationssysteme Tracking algorithms computer vision digital elevation model image analysis image understanding satellite

Editors and affiliations

  • Armin Gruen
    • 1
  • Olaf Kuebler
    • 2
  • Peggy Agouris
    • 1
  1. 1.Institute of Geodesy & PhotogrammetryETH-HoenggerbergZürichSwitzerland
  2. 2.Communications Technology LaboratoryETH-ZentrumZürichSwitzerland

Bibliographic information

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