Real-Time Tracking of Complex Structures for Visual Servoing

  • Tom Drummond
  • Roberto Cipolla
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1883)


This paper presents a visual servoing system which incorporates a novel three-dimensional model-based tracking system. This tracking system extends constrained active contour tracking techniques into three dimensions, placing them within a Lie algebraic framework. This is combined with modern graphical rendering technology to create a system which can track complex three dimensional structures in real time at video frame rate (25 Hz) on a standard workstation without special hardware. The system is based on an internal CAD model of the object to be tracked which is rendered using binary space partition trees to perform hidden line removal. The visible features are identified on-line at each frame and are tracked in the video feed. Analytical and statistical edge saliency are then used as a means of increasing the robustness of the tracking system.


Tracking System Plane Partition British Machine Vision Euclidean Transformation Video Frame Rate 
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.
    M. Armstrong and A. Zisserman. Robust object tracking. In Proceedings of Second Asian Conference on Computer Vision, pages 58–62, 1995.Google Scholar
  2. 2.
    R. Basri, E. Rivlin, and I. Shimshoni. Visual homing: Surfing on the epipoles. In Proceedings of International Conference on Computer Vision (ICCV’ 98), pages 863–869, 1998.Google Scholar
  3. 3.
    R. Cipolla and A. Blake. Image divergence and deformation from closed curves. International Journal of Robotics Research, 16(1):77–96, 1997.CrossRefGoogle Scholar
  4. 4.
    N. Daucher, M. Dhome, J. T. Lapresté, and G. Rives. Modelled object pose estimation abd tracking by monocular vision. In Proceedings of the British Machine Vision Conference, pages 249–258, 1993.Google Scholar
  5. 5.
    T. Drummond and R. Cipolla. Visual tracking and control using Lie algebras. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR’99), volume 2, pages 652–657, 1999.Google Scholar
  6. 6.
    T. Drummond and R. Cipolla. Real-time tracking of complex structures with on-line camera calibration. In Proceedings of the 10th British Machine Vision Conference (BMVC’99), 1999. to appear.Google Scholar
  7. 7.
    B. Espiau, F. Chaumette, and P. Rives. A new approach to visual servoing in robotics. IEEE T-Robotics and Automation, 8(3), 1992.Google Scholar
  8. 8.
    M. Haag and H-H. Nagel. Tracking of complex driving manoeuvres in traffic image sequences. Image and Vision Computing, 16:517–527, 1998.CrossRefGoogle Scholar
  9. 9.
    G. Hager, G. Grunwald, and K. Toyama. Feature-based visual servoing and its application to telerobotics. In V. Graefe, editor, Intelligent Robotic Systems. Elsevier, 1995.Google Scholar
  10. 10.
    C. Harris. Tracking with rigid models. In V. Blake editor, Active Vision, chapter 4, pages 59–73. MIT Press, 1992.Google Scholar
  11. 11.
    C. Harris. Geometry from visual motion. In A. Bedake, editor, Active Vision, chapter 16, pages 263–284. MIT Press, 1992.Google Scholar
  12. 12.
    P. J. Huber. Robust Statistic. Wiley series in probability and mathematical statistics. Wiley, 1981.Google Scholar
  13. 13.
    S. Hutchinson, G.D. Hager, and P.I. Corke. A tutorial on visual servo control. IEEET-Robotics and Automation, 12(5):651–670, 1996.CrossRefGoogle Scholar
  14. 14.
    M. Isard and A. Blake. CONDENSATION-conditional density propagation for visual tracking. International Journal of Computer Vision, 29(1):5–28, 1998.CrossRefGoogle Scholar
  15. 15.
    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
  16. 16.
    J. MacCormick and A. Blake. Spatial dependence in the observation of visual contours. In Proceedings of the Fifth European Conference on Computer vision (ECCV’98), pages 765–781, 1998.Google Scholar
  17. 17.
    E. Marchand, P. Bouthemy, F. Chaumette, and V. Moreau. Robust real-time visual tracking using a 2d-3d model-based approach. In Proceedings of IEEE International Conference on Computer Vision (ICCV’99), 1999. to appear.Google Scholar
  18. 18.
    M. Paterson and F. Yao. Efficient binary space partitions for hidden surface removal and solid modeling. Discrete and Computational Geometry, 5(5):485–503, 1990.zbMATHMathSciNetGoogle Scholar
  19. 19.
    D. Terzopoulos and R. Szeliski. Tracking with Kalman snakes. In A. Blake, editor, Active Vision, chapter 1, pages 3–20. MIT Press, 1992.Google Scholar
  20. 20.
    A. D. Worrall, G. D. Sullivan, and K. D. Baker. Pose refinement of active models using forces in 3d. In J. Eklundh, editor, Proceedings of the Third European Conference on Computer vision (ECC’ 94), volume 2, pages 341–352, May 1994.Google Scholar
  21. 21.
    P. Wunsch and G. Hirzinger. Real-time visual tracking of 3-d objects with dynamic handling of occlusion. In Proceedings of the 1997 International Conference on Robotics and Automation, pages 2868–2873, 1997.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Tom Drummond
    • 1
  • Roberto Cipolla
    • 1
  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUK

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