Contour/Texture Approach for Visual Tracking

  • Lucie Masson
  • Frédéric Jurie
  • Michel Dhome
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)


In this article, the problem of real-time hybrid contour/texture tracking for planar objects is addressed. On one hand, a lot of methods have been proposed to track objects from their contours. On the other hand, numerous other tracking algorithms deal with texture. In real situations, objects can unfortunately rarely be divided so clearly. Therefore, an hybrid tracking approach, able to mix texture and contour information, appears to be very useful.

The proposed approach is very simple and efficient. It is based on image differences, which are the differences between object aspects in the image and aspects predicted using a parametric transformation model. Knowing a difference image, the proposed algorithm only need a matrix multiplication to estimate motion parameters. This is possible due to the use of an off-line learning stage.


  1. 1.
    D. Comaniciu, V. Ramesh, and P. Meer. Real-time tracking of non-rigid objects using mean shift. In CVPR00, pages II: 142–149, 2000.Google Scholar
  2. 2.
    T. Drummond and R. Cipolla. Real-time tracking of complex structures with on-line camera calibration. IVC, 20(5–6):427–433, March 2002.CrossRefGoogle Scholar
  3. 3.
    G.D. Hager and P.N. Belhumeur. Efficient region tracking with parametric models of geometry and illumination. IEEE Trans. Pattern Analysis and Machine Intelligence, 20(10):1025–1039, October 1998.CrossRefGoogle Scholar
  4. 4.
    C. Harris and M. Stephens. A combined corner and edge detector. In 4th Alvey Vision Conference, pages 147–151, Mancherster, 1988.Google Scholar
  5. 5.
    A. D. Jepson, D.J. Fleet, and T.F. El-Maraghi. Robust on-line appearance models for visual tracking. In IEEE Conference on Computer Vision and Pattern Recognition, pages pp. 415–422, 2001.Google Scholar
  6. 6.
    F. Jurie and M. Dhome. Real time 3d template matching. In Computer Vision and Pattern Recongition, pages (I)791–797, Hawai, December 2001.Google Scholar
  7. 7.
    F. Jurie and M. Dhome. Real time template matching. In Proc. IEEE International Conference on Computer vision, pages 544–549, Vancouver, Canada, July 2001.Google Scholar
  8. 8.
    F. Jurie and M. Dhome. Hyperplane approximation for template matching. IEEE Trans. Pattern Analysis and Machine Intelligence, 24(7):996–1000, 2002.CrossRefGoogle Scholar
  9. 9.
    H. Kollnig and H.H. Nagel. 3d pose estimation by directly matching polyhedral models to gray value gradients. International Journal of Computer Vision, 23(3):283–302, 1997.CrossRefGoogle Scholar
  10. 10.
    M. La Cascia, S. Sclaroif, and V. Athitsos. Fast, reliable head tracking under varying illumination: An approach based on registration of textured-mapped 3d models. PAMI, 22(4):322–336, April 2000.Google Scholar
  11. 11.
    D.G. Lowe. Robust model-based motion tracking through the integration of search and estimation. International Journal of Computer Vision, 8(2):113–122, 1992.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Lucie Masson
    • 1
  • Frédéric Jurie
    • 1
  • Michel Dhome
    • 1
  1. 1.LASMEA - CNRS UMR 6602Université Blaise-PascalAubière

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