Planar Surface Detection in Image Pairs Using Homographic Constraints

  • Qiang He
  • Chee-hung Henry Chu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4291)


Planar surfaces are important characteristics in man-made environments and have been successfully applied to camera calibration and interactive modeling. We develop a method for detecting planes in image pairs under epipolar constraints using planar homographies. In order to extract the whole planes, the normalized cut method is used to segment the original images. We pick those segmented regions that best fit a triangulation of the homography inliers as the detected planes. We illustrate the algorithm’s performance using gray-level and color image pairs.


Augmented Reality Planar Surface Image Pair Delaunay Triangulation Camera Calibration 
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.
    Lourakis, M., Argyros, A., Orphanoudakis, S.: Detecting planes in an uncalibrated image pair. In: Proc. BMVC 2002, vol. 2, pp. 587–596 (2002)Google Scholar
  2. 2.
    Sturm, P., Maybank, S.: On plane-based camera calibration: A general algorithm, singularities, applications. In: IEEE Conf. Computer Vision and Pattern Recognition, pp. 432–437 (1999)Google Scholar
  3. 3.
    Schindler, K.: Generalized use of homographies for piecewise planar reconstruction. In: Bigun, J., Gustavsson, T. (eds.) SCIA 2003. LNCS, vol. 2749, Springer, Heidelberg (2003)CrossRefGoogle Scholar
  4. 4.
    Baillard, C., Zisserman, A.: A plane-sweep strategy for the 3d reconstruction of buildings from multiple images. In: Proc. 19th ISPRS Congress and Exhibition, pp. 56–62 (2000)Google Scholar
  5. 5.
    Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2003)Google Scholar
  6. 6.
    Criminisi, A., Reid, I., Zisserman, A.: A plane measuring device. Image and Vision Computing 17, 625–634 (1999)CrossRefGoogle Scholar
  7. 7.
    Simon, G., Fitzgibbon, A., Zisserman, A.: Markerless tracking using planar structures in the scene. In: Proc. Int. Symp. Augmented Reality (2000)Google Scholar
  8. 8.
    Zoghlami, I., Faugeras, O., Deriche, R.: Using geometric corners to build a 2D mosaic from a set of images. In: Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 420–425 (1997)Google Scholar
  9. 9.
    Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 888–905Google Scholar
  10. 10.
    Sloan, S.W., Houlsby, G.T.: An implementation of Watson’s algorithm for computing 2-D Delauney triangulations. Advanced Engineering Software 6 (1984)Google Scholar
  11. 11.
    O’Rourke, J.: Computational Geometry in C, 1st edn. Cambridge University Press, Cambridge (1994)zbMATHGoogle Scholar
  12. 12.
    Harris, C., Stephens, M.: A combined corner and edge detector. In: Proc. 4th Alvey Vision Conference, pp. 147–151 (1988)Google Scholar
  13. 13.
    Fischler, M.A., Bolles, R.C.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24, 381–395 (1981)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Qiang He
    • 1
  • Chee-hung Henry Chu
    • 1
  1. 1.Center for Advanced Computer StudiesThe University of Louisiana at LafayetteLafayetteU.S.A.

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