Advertisement

Efficient 3-D scene visualization by image extrapolation

  • Tomáš Werner
  • Tomáš Pajdla
  • Václav Hlaváč
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1407)

Abstract

Image-based scene representation is believed to be an alternative to the 3-D model reconstruction and rendering. In attempt to compare generality of image-based and model-based approaches we argue that it is plausible to distinguish three approaches to 3-D scene visualization: image interpolation, image extrapolation, and 3-D model reconstruction and rendering. We advocate that image extrapolation is a useful trade-off between simple but limited interpolation and general but difficult 3-D model reconstruction and rendering. Image extrapolation is able to visualize correctly the part of a 3-D scene that is visible from two reference images. In fact, it is equivalent to reconstructing a projective 3-D model from two reference images and rendering it. In the second part of the work, we present an algorithm for rendering a projective model. Our approach is more efficient than the ray-tracing-like algorithm by Laveau and Faugeras [6]. We show that visibility can be solved by z-buffering, and that virtual images can be synthesized by transferring triangles from a reference image via a homography or an affinity. Such algorithms are often supported by hardware on graphics work stations, which makes a step towards the real-time synthesis. The results are presented for real scenes.

Keywords

Reference Image Image Point Model Reconstruction Virtual Image Virtual Camera 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Shenchang Eric Chen and Lance Williams. View interpolation for image synthesis. In James T. Kajiya, editor, Computer Graphics (SIGGRAPH '93 Proceedings), volume 27, pages 279–288, August 1993.Google Scholar
  2. 2.
    O. Faugeras and B. Mourrain. On the geometry and algebra of the point and line correspondences between N images. In Proceedings of the 5th International Conference on Computer Vision, pages 951–956, Boston, USA, June 1995. IEEE.Google Scholar
  3. 3.
    Olivier D. Faugeras, Q. T. Luong, and S. J. Maybank. Camera self-calibration: Theory and experiments. In European Conference on Computer Vision, pages 321–333, 1992.Google Scholar
  4. 4.
    R. I. Hartley. A linear method for reconstruction from lines and points. In Proceedings of the 5th International Conference on Computer Vision, pages 882–887, Boston USA, June 1995. IEEE Computer Society Press.Google Scholar
  5. 5.
    R. Kumar, P. Anadan, M. Irani, J. Bergen, and K. Hanna. Representation of scenes from collection of images. In Proceedings of the Visual Scene Representation Workshop, Boston, MA., USA, June 24, pages 10–17. IEEE Computer Society Press, 1995.Google Scholar
  6. 6.
    S. Laveau and O. Faugeras. 3-D scene representation as a collection of images. In Proc. of 12th International Conf. on Pattern Recognition, Jerusalem, Israel, pages 689–691, October 9–13 1994.Google Scholar
  7. 7.
    S. Laveau and O. Faugeras. Oriented projective geometry for computer vision. In Proceedings of the 4th European Conference on Computer Vision'96, volume I, pages 147–156. Springer-Verlag, April 1996.Google Scholar
  8. 8.
    Leonard McMillan and Gary Bishop. Plenoptic modeling: An image-based rendering system. In Robert Cook, editor, SIGGRAPH'95 Conference Proceedings, pages 39–46. Addison Wesley, August 1995.Google Scholar
  9. 9.
    Charlie Rothwell, Gabriela Csurka, and Olivier Faugeras. A comparison of projective reconstruction methods for pairs of views. Technical Report 2538, INRIA, Sophia-Antipolis, France, April 1995.Google Scholar
  10. 10.
    S. M. Seitz and C. R. Dyer. Physically-valid view synthesis by image interpolation. In Proceedings of the Visual Scene Representation Workshop, Boston, MA., USA, June 24, pages 18–27. IEEE Computer Society Press, 1995.Google Scholar
  11. 11.
    A. Shashua. On geometric and algebraic aspects of 3D affine and projective structures from perspective 2D views. Technical Report AI Memo No. 1405, Massachusetts Institute of Technology, Artifical Intelligence Laboratory, July 1993.Google Scholar
  12. 12.
    A. Shashua and M. Werman. Trilinearity of three perspective views and its associated tensor. In Proceedings of the 5th International Conference on Computer Vision, pages 920–925. IEEE Computer Society Press, May 1995.Google Scholar
  13. 13.
    M. Spetsakis and J. Alomoinos. A unified theory of structure from motion. In Proceedigs ARPA Image Understanding Workshop, pages 271–283, Pittsburg, PA, USA, 1990.Google Scholar
  14. 14.
    S. Ullman and R. Basri. Recognition by linear combination of models. IEEE Transactions of Pattern Analysis and Machine Intelligence, 13(10):992–1005, October 1991.CrossRefGoogle Scholar
  15. 15.
    T. Werner, R.D. Hersch, and V. Hlaváč. Rendering real-world objects using view interpolation. In Proceedings of the 5th International Conference on Computer Vision, pages 957–962, Boston, USA, June 1995. IEEE Computer Society Press.Google Scholar
  16. 16.
    T. Werner, V. Hlaváč, A. Leonardis, and T. Pajdla. Selection of reference views for image-based representation. In Proceedings of the 13th International Conference on Pattern Recognition, volume I — Track A: Computer Vision, pages 73–77, Vienna, Austria, August 1996. IEEE Computer Society Press, Los Alamitos, CA., USA.Google Scholar
  17. 17.
    Tomáš Werner, Tomáš Pajdla, and Václav Hlaváč. Correspondence by tracking edges in a dense sequence for image-based scene representation. In Proceedings of the Czech Pattern Recognition Workshop '97, pages 64–68, Milovy, Czech Republic, Feb 1997. Czech Pattern Recognition Society. Available from http://cmp.felk.cvut.cz.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Tomáš Werner
    • 1
  • Tomáš Pajdla
    • 1
  • Václav Hlaváč
    • 1
  1. 1.Center for Machine Perception, Faculty of Electrical EngineeringCzech Technical UniversityPrague 2Czech Republic

Personalised recommendations