Skip to main content
Log in

Lie Algebra and System Identification Techniques for 3D Rigid Motion Estimation and Monocular Tracking

  • Published:
Journal of Mathematical Imaging and Vision Aims and scope Submit manuscript

Abstract

This paper addresses the parameters’ estimation of 2D and 3D transformations. For the estimation we present a method based on system identification theory, we named it the “A-method”. The transformations are considered as elements of the Lie group GL(n) or one of its subgroups. We represent the transformations in terms of their Lie Algebra elements. The Lie algebra approach assures to follow the shortest path or geodesic in the involved Lie group. To prove the potencial of our method, two experiments are presented. The first one is a monocular estimation of 3D rigid motion of an object in the visual space. With this aim, the six parameters of the rigid motion are estimated based on measurements of the six parameters of the affine transformation in the image. Secondly, we present the estimation of the affine or projective transformations involved in monocular region tracking.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. A. Azarbayejani and A. Pentland, “Recursive estimation of motion, structure and focal lenght,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 17, No. 6, pp. 562–575, 1995.

    Article  Google Scholar 

  2. S. Baker and I. Matthews, “Lucas-kanade 20 years on: A unifying framework,” International Journal of Computer Vision, Vol. 56, No. 3, pp. 221–255, 2004.

    Article  Google Scholar 

  3. T.J. Broida, S. Chandrashekhar, and R. Chellappa, “Recursive 3-d motion estimation from a monocular image sequence,” IEEE Trans. Aerosp. Electron. Syst.,Vol. 26, No. 4, pp. 639–656, 1990.

    Article  Google Scholar 

  4. H. Chiuso, P. Favaro, and S. Soatto, “Structure from motion and causally intergated over time,” IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 24, No. 4, pp. 523–535, 2002.

    Article  Google Scholar 

  5. C. Colombo and B. Allota, “Image-based robot task planning and control using compact visual representation.” IEEE Trans. Syst. Man Cybern. Part A: Syst. Humans, Vol. 29, No. 1, pp. 92–100, 1999.

    Article  Google Scholar 

  6. K. Daniilidis, “Fixation simplifies 3d motion estimation,” Comput. Vis. Image Underst., Vol. 68, No. 2, pp. 158–169, 1997.

    Article  Google Scholar 

  7. T. Drummond and R. Cipolla, “Application of lie algebras to visual servoing,” Intl. J. Comp. Vision, Vol. 37, No. 1, pp. 21–41, 2000.

    Article  MATH  Google Scholar 

  8. T. Frankel, The Geometry of Physics: an Introduction. Cambridge University Press: Cambridge, UK, 1997.

    Google Scholar 

  9. G.D. Hager and P.N. Belhumeur, “Efficient region tracking with parametric models of geometry and illumination,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 20, No. 10, pp. 1025–1039, 1998.

    Article  Google Scholar 

  10. B.C. Hall, Lie Groups, Lie Algebras, and Representations: an Elementary Introduction. Springer-Verlag: New York, NY, USA, 2003.

    Google Scholar 

  11. M.A. Isard and A. Blake, “Condensation – conditional density propagation for visual tracking,” Intl. J. Comp. Vision, Vol. 29, No. 1, pp. 5–28, 1998.

    Article  Google Scholar 

  12. F. Jurie and M. Dhome, “Hyperplane approximation for template matching,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 24, No. 7, pp. 996–1000, 2002.

    Article  Google Scholar 

  13. B.D. Lucas and T. Kanade, “An iterative image registration technique with an application to stereo vision,” in: Proceedings of the 1981 DARPA Image Understanding Workshop, 1981, pp. 121–130.

  14. S. Mann and R.W. Picard, “Video orbits of the projective group: A simple approach to featureless estimation of parameters,” IEEE Trans. Image Process., Vol. 6, No. 9, pp. 1281–1295, 1997.

    Article  Google Scholar 

  15. F.C. Park, J.E. Bobrow, and S. Ploen, “A lie group formulation of robot dynamics,” Int. J. Rob. Res., Vol. 14, No. 6, pp. 609–618, 1995.

    Google Scholar 

  16. A. Ruf and R. Horaud, “Visual servoing of robot manipulators, part i: Projective kinematics,” Intl. J. Rob. Res., Vol. 18, No. 11, pp. 1101–1118, 1999.

    Article  Google Scholar 

  17. J. Shi and C. Tomasi, “Good features to track,” in: Proc. IEEE Int. Conf. Comp. Vision and Pattern Recogn., pp. 593–600, 1994.

  18. H. Shum and R. Szeliski, “Construction of panoramic image mosaics with global and local alignment,” International Journal of Computer Vision, Vol. 16, No. 1, pp. 63–84, 2000.

    Google Scholar 

  19. H.J.R. Thomas, M. Martinetz, and K.J. Schulten, “Three-dimensional neural net for learning visuomotor coordination of a robot arm,” IEEE Trans. Neural Netw., Vol. 1, No. 1, pp. 131–136, 1990.

    Article  Google Scholar 

  20. T. Tommasini, A. Fusiello, E. Trucco, and V. Roberto, “Making good features track better,” in: Proc. IEEE Int. Conf. Comp. Vision and Pattern Recogn., pp. 178–183, 1998.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jaime Ortegón-Aguilar.

Additional information

Jaime Ortegón-Aguilar received his degree in computer sciences at the Universidad Autonoma de Yucatan in Merida, Mexico in 2000. He earned his M.Sc. degree at the Cinvestav in Guadalajara, Mexico in 2002. He received his PhD degree from Cinvestav in 2006. His research interests include image processing, computer vision, robotics and applications of geometric algebra.

Eduardo Jose Bayro-Corrochano gained his Ph.D. in Cognitive Computer Science in 1993 from the University of Wales at Cardiff. From 1995 to 1999 he has been Researcher and Lecturer at the Institute for Computer Science, Christian Albrechts University, Kiel, Germany, working on applications of geometric Clifford algebra to cognitive systems. At present is a full professor at CINVESTAV Unidad Guadalajara, México, Department of Electrical Engineering and Computer Science.

His current research interest focuses on geometric methods for artificial perception and action systems. It includes geometric neural networks, visually guided robotics, humanoids, color image processing, Lie bivector algebras for early vision and robot maneuvering. He developed the quaternion wavelet transform for quaternion multi-resolution analysis using the phase concept. He is associate editor of Robotics and Journal of Advanced Robotic Systems and member of the editorial board of Journal of Pattern Recognition, Journal of Mathematical Imaging and Vision, Iberoamerican Journal of Computer and Systems and Journal of Theoretical and Numerical Approximation. He is editor and author of the following books: Geometric Computing for Perception Action Systems, E. Bayro-Corrochano, Springer Verlag, 2001; Geometric Algebra with Applications in Science and Engineering, E. Bayro-Corrochano and G. Sobczyk (Eds.), Birkhauser 2001; Handbook of Geometric Computing for Pattern Recognition, Computer Vision, Neurocomputing and Robotics, E. Bayro-Corrochano, Springer Verlag, 2005. He has published over 120 refereed journal, book chapters and conference papers. He is fellow of the IAPR society.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ortegón-Aguilar, J., Bayro-Corrochano, E. Lie Algebra and System Identification Techniques for 3D Rigid Motion Estimation and Monocular Tracking. J Math Imaging Vis 25, 173–185 (2006). https://doi.org/10.1007/s10851-006-9697-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10851-006-9697-6

Keywords

Navigation