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Similarity Measure for Corner Redetection

  • Christoph Stock
  • Axel Pinz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)

Abstract

Corners are important image-features for tracking applications. We present a new method to calculate the similarity of corners, which is used to improve the redetection performance of corner-based tracking applications. It is a simple and fast method to calculate a scaled measure of similarity, which aggregates basic corner features like dihedral angle, cornerness, and corner orientation. Experimental results verify that the similarity measure is well suited for tracking applications.

References

  1. 1.
    Manmohan K. Chandraker, Christoph Stock, and Axel Pinz. Real-time camera pose in a room. In 3rd Intern. Conference on Computer Vision Systems, ICVS 2003, pages 98–110, Graz, Austria, April 2003.Google Scholar
  2. 2.
    C. Harris and M. Stephens. A combined corner and edge detector. In Proc. of the 4th Alvey Vision Conference, pages 189–192, Manchester, 1988.Google Scholar
  3. 3.
    J. Bigun and G. H. Granlund. Optimal orientation detection of linear symmetry. In ICCV, volume 1, pages 433–438, London, June 1987.Google Scholar
  4. 4.
    C. F. Olson and D. P. Huttenlocher. Automatic target recognition by oriented edge pixels. In IEEE Transaction on Image Processing, 6(1), pages 103–113, January 1997.CrossRefGoogle Scholar
  5. 5.
    M. Ribo, H. Ganster, M. Brandner, P. Lang, Ch. Stock, and A. Pinz. Hybrid tracking for outdoor AR applications. IEEE Computer Graphics and Applications Magazine, 22(6):54–63, 2002.CrossRefGoogle Scholar
  6. 6.
    Karl Rohr. Recognizing Corners by Fitting Parametric Models. International Journal of Computer Vision, 9(3):213–230, 1992.CrossRefGoogle Scholar
  7. 7.
    Yin S. and Balchen J. G. Corner characterization by statistical analysis of gradient directions. In Proc. of Int. Conf. on Image Processing, volume 2, pages 760–763, 1997.CrossRefGoogle Scholar
  8. 8.
    Cordelia Schmid and Roger Mohr. Local greyvalue invariants for image retrieval. IEEE Trans. on Pattern Analysis and Machine Intelligence, 19(5):530–535, 1997.CrossRefGoogle Scholar
  9. 9.
    P. Smith, D. Sinclair, R. Cipolla, and K. Wood. Effective corner matching. In Proc. 9th British Machine Vision Conference, BMVC 1998, pages 545–556, Southampton, September 1998.Google Scholar
  10. 10.
    Ch. Stock, U. Mühlmann, M. K. Chandraker, and A. Pinz. Subpixel corner detection for tracking applications using CMOS camera technology. In Proc. of 26th Workshop of the Austrian Association for Pattern Recognition(ÖAGM/AAPR), volume 160, pages 191–199, Graz, Austria, September 2002.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Christoph Stock
    • 1
  • Axel Pinz
    • 1
  1. 1.Institute of Electrical Measurement and Measurement Signal ProcessingGraz University of TechnologyAustria

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