Detecting 3-D parallel lines for perceptual organization

  • Xavier Lebègue
  • J. K. Aggarwal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)


This paper describes a new algorithm to simultaneously detect and classify straight lines according to their orientation in 3-D. The fundamental assumption is that the most “interesting” lines in a 3-D scene have orientations which fall into a few precisely defined categories. The algorithm we propose uses this assumption to extract the projection of straight edges from the image and to determine the most likely corresponding orientation in the 3-D scene. The extracted 2-D line segments are therefore “perceptually” grouped according to their orientation in 3-D. Instead of extracting all the line segments from the image before grouping them by orientation, we use the orientation data at the lowest image processing level, and detect segments separately for each predefined 3-D orientation. A strong emphasis is placed on real-world applications and very fast processing with conventional hardware.


Line Segment Mobile Robot Perceptual Organization Gradient Orientation World Coordinate System 
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.


  1. 1.
    S. T. Barnard. Interpreting perspective images. Artificial Intelligence, 21(4):435–462, November 1983.Google Scholar
  2. 2.
    J. B. Burns, A. R. Hanson, and E. M. Riseman. Extracting straight lines. IEEE Trans. on Pattern Analysis and Machine Intelligence, 8(4):425–455, July 1986.Google Scholar
  3. 3.
    P. Kahn, L.Kitchen, and E. M. Riseman. A fast line finder for vision-guided robot navigation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 12(11):1098–1102, November 1990.Google Scholar
  4. 4.
    X. Lebègue and J. K. Aggarwal. Extraction and interpretation of semantically significant line segments for a mobile robot. To appear in Proc. IEEE Int. Conf. Robotics and Automation, Nice, France, May 1992.Google Scholar
  5. 5.
    D. G. Lowe. Perceptual Organization and Visual Recognition. Kluwer Academic Publishers, 1985.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Xavier Lebègue
    • 1
  • J. K. Aggarwal
    • 1
  1. 1.Computer and Vision Research Center, Dept. of Electrical and Computer Engr.The University of Texas at AustinAustinUSA

Personalised recommendations