Skip to main content

Trilinear tensor: The fundamental construct of multiple-view geometry and its applications

  • Processing of the 3D Visual Space
  • Conference paper
  • First Online:
Algebraic Frames for the Perception-Action Cycle (AFPAC 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1315))

Abstract

The topic of representation, recovery and manipulation of three-dimensional (3D) scenes from two-dimensional (2D) images thereof, provides a fertile ground for both intellectual theoretically inclined questions related to the algebra and geometry of the problem and to practical applications such as Visual Recognition, Animation and View Synthesis, recovery of scene structure and camera ego-motion, object detection and tracking, multi-sensor alignment, etc.

The basic materials have been known since the turn of the century, but the full scope of the problem has been under intensive study since 1992, first on the algebra of two views and then on the algebra of multiple views leading to a relatively mature understanding of what is known as “multilinear matching constraints”, and the “trilinear tensor” of three or more views.

The purpose of this paper is, first and foremost, to provide a coherent framework for expressing the ideas behind the analysis of multiple views. Secondly, to integrate the various incremental results that have appeared on the subject into one coherent manuscript.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. Avidan and A. Shashua. Unifying two-view and three-view geometry. Technical report, Hebrew University of Jerusalem, November 1996.

    Google Scholar 

  2. S. Avidan and A. Shashua. View synthesis in tensor space. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Puerto Rico, June 1997.

    Google Scholar 

  3. P. Beardsley, P. Torr, and A. Zisserman. 3D model acquisition from extended image sequences. In Proceedings of the European Conference on Computer Vision, April 1996.

    Google Scholar 

  4. S. Carlsson. Duality of reconstruction and positioning from projective views. In Proceedings of the workshop on Scene Representations, Cambridge, MA., June 1995.

    Google Scholar 

  5. R. Deriche, Z. Zhang, Q.T. Luong, and O.D. Faugeras. Robust recovery of the epipolar geometry for an uncalibrated stereo rig. In Proceedings of the European Conference on Computer Vision, pages 567–576, Stockholm, Sweden, May 1994. Springer-Verlag, LNCS 800.

    Google Scholar 

  6. O.D. Faugeras. What can be seen in three dimensions with an uncalibrated stereo rig? In Proceedings of the European Conference on Computer Vision, pages 563–578, Santa Margherita Ligure, Italy, June 1992.

    Google Scholar 

  7. O.D. Faugeras. Stratification of three-dimensional vision: projective, affine and metric representations. Journal of the Optical Society of America, 12(3):465–484, 1995.

    Google Scholar 

  8. O.D. Faugeras and B. Mourrain. On the geometry and algebra of the point and line correspondences between N images. In Proceedings of the International Conference on Computer Vision, Cambridge, MA, June 1995.

    Google Scholar 

  9. O.D. Faugeras and T. Papadopoulo. A nonlinear method for estimating the projective geometry of three views. Submitted, June 1997.

    Google Scholar 

  10. R. Hartley. Lines and points in three views — a unified approach. In Proceedings of the ARPA Image Understanding Workshop, Monterey, CA, November 1994.

    Google Scholar 

  11. R. Hartley. A linear method for reconstruction from lines and points. In Proceedings of the International Conference on Computer Vision, pages 882–887, Cambridge, MA, June 1995.

    Google Scholar 

  12. A. Heyden. Reconstruction from image sequences by means of relative depths. In Proceedings of the International Conference on Computer Vision, pages 1058–1063, Cambridge, MA, June 1995.

    Google Scholar 

  13. M. Irani and P. Anandan. Parallax geometry of pairs of points for 3D scene analysis. In Proceedings of the European Conference on Computer Vision, LNCS 1064, pages 17–30, Cambridge, UK, April 1996. Springer-Verlag.

    Google Scholar 

  14. D.W. Jacobs. Matching 3D models to 2D images. International Journal of Computer Vision, 21(12):123–153, January 1997.

    Article  Google Scholar 

  15. H.C. Longuet-Higgins. A computer algorithm for reconstructing a scene from two projections. Nature, 293:133–135, 1981.

    Google Scholar 

  16. Torr P.H.S., Zisserman A., and Murray D. Motion clustering using the trilinear constraint over three views. In Workshop on Geometrical Modeling and Invariants for Computer Vision. Xidian University Press., 1995.

    Google Scholar 

  17. A. Shashua. Projective structure from uncalibrated images: structure from motion and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(8):778–790, 1994.

    Article  Google Scholar 

  18. A. Shashua. Algebraic functions for recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(8):779–789, 1995.

    Article  Google Scholar 

  19. A. Shashua. Trilinear tensor: The fundamental construct of multiple-view geometry and its applications. Submitted for journal publication, June 1997.

    Google Scholar 

  20. A. Shashua and P. Anandan. The generalized trilinear constraints and the uncertainty tensor. In Proceedings of the ARPA Image Understanding Workshop, Palm Springs, CA, February 1996.

    Google Scholar 

  21. A. Shashua and S. Avidan. The rank4 constraint in multiple view geometry. In Proceedings of the European Conference on Computer Vision, Cambridge, UK, April 1996.

    Google Scholar 

  22. A. Shashua and S.J. Maybank. Degenerate n point configurations of three views: Do critical surfaces exist? Technical Report TR 96-19, Hebrew University of Jerusalem, November 1996.

    Google Scholar 

  23. A. Shashua and N. Navab. Relative affine structure: Canonical model for 3D from 2D geometry and applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(9):873–883, 1996.

    Article  Google Scholar 

  24. A. Shashua and M. Werman. Trilinearity of three perspective views and its associated tensor. In Proceedings of the International Conference on Computer Vision, June 1995.

    Google Scholar 

  25. M.E. Spetsakis and J. Aloimonos. Structure from motion using line correspondences. International Journal of Computer Vision, 4(3):171–183, 1990.

    Article  Google Scholar 

  26. M.E. Spetsakis and J. Aloimonos. A unified theory of structure from motion. In Proceedings of the ARPA Image Understanding Workshop, 1990.

    Google Scholar 

  27. G. Stein and A. Shashua. Model based brightness constraints: On direct estimation of structure and motion. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Puerto Rico, June 1997.

    Google Scholar 

  28. C. Tomasi and T. Kanade. Shape and motion from image streams-a factorization method. International Journal of Computer Vision, 9(2):137–154, 1992.

    Article  Google Scholar 

  29. B. Triggs. Matching constraints and the joint image. In Proceedings of the International Conference on Computer Vision, pages 338–343, Cambridge, MA, June 1995.

    Google Scholar 

  30. S. Ullman and R. Basri. Recognition by linear combination of models. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-13:992–1006, 1991. Also in M.LT AI Memo 1052, 1989.

    Google Scholar 

  31. D. Weinshall, M. Werman, and A. Shashua. Duality of multi-point and multi-frame geometry: Fundamental shape matrices and tensors. In Proceedings of the European Conference on Computer Vision, LNCS 1065, pages 217–227, Cambridge, UK, April 1996. Springer-Verlag.

    Google Scholar 

  32. J. Weng, T.S. Huang, and N. Ahuja. Motion and structure from line correspondences: Closed form solution, uniqueness and optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(3), 1992.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Gerald Sommer Jan J. Koenderink

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Shashua, A. (1997). Trilinear tensor: The fundamental construct of multiple-view geometry and its applications. In: Sommer, G., Koenderink, J.J. (eds) Algebraic Frames for the Perception-Action Cycle. AFPAC 1997. Lecture Notes in Computer Science, vol 1315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017868

Download citation

  • DOI: https://doi.org/10.1007/BFb0017868

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63517-8

  • Online ISBN: 978-3-540-69589-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics