Multiview Registration of 3D Scenes by Minimizing Error between Coordinate Frames

  • Gregory C. Sharp
  • Sang W. Lee
  • David K. Wehe
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2351)


This paper addresses the problem of large scale multiview registration of range images captured from unknown viewing directions. To reduce the computational burden, we decouple the local problem of pairwise registration on neighboring views from the global problem of distribution of accumulated errors. We define the global problem over the graph of neighboring views, and we show that this graph can be decomposed into a set of cycles such that the optimal transformation parameters for each cycle can be solved in closed form. We then describe an iterative procedure that can be used to integrate the solutions for the set of cycles across the graph. This method for error distribution does not require point correspondences between views, and therefore can be used together with robot odometry or any method of pairwise registration. Experimental results demonstrate the effectiveness of this technique on range images of an indoor facility.


Mobile Robot Span Tree Range Image Basis Cycle Partial Graph 
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.


  1. 1.
    R. Benjemaa and F. Schmitt. A solution for the registration of multiple 3-d point sets using unit quaternions. In European Conference on Computer Vision, 1998.Google Scholar
  2. 2.
    C. Berge. The Theory of Graphs and its applications. Barnes & Noble, Inc., 1962.Google Scholar
  3. 3.
    R. Bergevin, M. Soucy, H. Gagnon, and D. Laurendeau. Towards a general multiview registration technique. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(5):540–547, May 1996.Google Scholar
  4. 4.
    P.J. Besl and N.D. McKay. A method for registration of 3-d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(2):239–256, February 1992.Google Scholar
  5. 5.
    G. Blais and M.D. Levine. Registering multiview range data to create 3d computer objects. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17(8):820–824, August 1995.Google Scholar
  6. 6.
    C.S. Chen, Y.P. Hung, and J.B. Cheng. Ransac-based darces: A new approach to fast automatic registration of partially overlapping range images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(11):1229–1234, November 1999.Google Scholar
  7. 7.
    Y. Chen and G.G. Medioni. Object modeling by registration of multiple range images. Image and Vision Computing, 10(3):145–155, 1992.CrossRefGoogle Scholar
  8. 8.
    C. Dorai, J. Weng, and A.K. Jain. Optimal registration of object views using range data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(10):1131–1138, October 1997.Google Scholar
  9. 9.
    D.W. Eggert, A.W. Fitzgibbon, and R.B. Fisher. Simultaneous registration of multiple range views for use in reverse engineering of cad models. Computer Vision and Image Understanding, 69(3):253–272, March 1998.Google Scholar
  10. 10.
    O.D. Faugeras and M. Hebert. The representation, recognition, and locating of 3-d objects. International Journal of Robotics Research, 5(3):27–52, 1986.CrossRefGoogle Scholar
  11. 11.
    B.K.P. Horn. Closed form solutions of absolute orientation using unit quaternions. Journal of the Optical Society of America-A, 4(4):629–642, April 1987.Google Scholar
  12. 12.
    D.F. Huber. Automatic 3d modeling using range images obtained from unknown viewpoints. In International Conference on 3D Digital Imaging and Modeling, pages 153–160, May 2001.Google Scholar
  13. 13.
    Williams J. and Bennamoun M. A multiple view 3d registration algorithm with statistical error modeling. IEICE Transactions on Information and Systems, 83-D(8):1662–1670, August 2000.Google Scholar
  14. 14.
    A.E. Johnson. Surface landmark selection and matching in natural terrain. In Computer Vision and Pattern Recognition, volume 2, pages 413–420, 2000.Google Scholar
  15. 15.
    E.Y. Kang, I. Cohen, and G.G. Medioni. A graph-based global registration for 2d mosaics. In International Conference on Pattern Recognition, pages Vol I: 257–260, 2000.Google Scholar
  16. 16.
    F. Lu and E. Milios. Globally consistent range scan alignment for environment mapping. Autonomous Robots, 4(4):333–349, 1997.CrossRefGoogle Scholar
  17. 17.
    T. Masuda and N. Yokoya. A robust method for registration and segmentation of multiple range images. Computer Vision and Image Understanding, 61(3):295–307, May 1995.Google Scholar
  18. 18.
    C.F. Olson. Probabilistic self-localization for mobile robots. IEEE Transactions on Robotics and Automation, 16(1):55–66, February 2000.Google Scholar
  19. 19.
    X. Pennec. Multiple Registration and Mean Rigid Shapes-Application to the 3D case. In Image Fusion and Shape Variability Techniques (16th Leeds Annual Statistical (LASR) Workshop), pages 178–185, july 1996.Google Scholar
  20. 20.
    X. Pennec. Computing the mean of geometric features: Application to the mean rotation. Technical Report RR-3371, INRIA, 1998.Google Scholar
  21. 21.
    K. Pulli. Multiview registration for large data sets. In International Conference on 3D Digital Imaging and Modeling, pages 160–168, 1999.Google Scholar
  22. 22.
    H.S. Sawhney, S. Hsu, and R. Kumar. Robust video mosaicing through topology inference and local to global alignment. In European Conference on Computer Vision, pages 103–119, 1998.Google Scholar
  23. 23.
    G.C. Sharp, S.W. Lee, and D.K. Wehe. Toward multiview registration in frame space. In IEEE International Conference on Robotics and Automation, 2001.Google Scholar
  24. 24.
    G.C. Sharp, S.W. Lee, and D.K. Wehe. Invariant features and the registration of rigid bodies. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(1):90–102, January 2002.Google Scholar
  25. 25.
    G.C. Sharp, S.W. Lee, and D.K. Wehe. Registration of range images in the presence of occlusions and missing data. Technical report, University of Michigan, 2002.Google Scholar
  26. 26.
    H.Y. Shum and R. Szeliski. Systems and experiment paper: Construction of panoramic image mosaics with global and local alignment. International Journal of Computer Vision, 36(2):101–130, February 2000.Google Scholar
  27. 27.
    A.J. Stoddart and A. Hilton. Registration of multiple point sets. In International Conference on Pattern Recognition, page B6A.5, 1996.Google Scholar
  28. 28.
    S. Thrun, D. Fox, and W. Burgard. A probabilistic approach to concurrent mapping and localization for mobile robots. Machine Learning, 31(1–3):29–53, 1998.zbMATHCrossRefGoogle Scholar
  29. 29.
    M. Trobina. Error model of a coded-light range sensor. Technical Report BIWI-TR-164, Communication Technology Laboratory, Image Science Group, ETH Zurich, 1995.Google Scholar
  30. 30.
    Z.Y. Zhang. Iterative point matching for registration of free-form curves and surfaces. International Journal of Computer Vision, 13(2):119–152, October 1994.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Gregory C. Sharp
    • 1
  • Sang W. Lee
    • 2
  • David K. Wehe
    • 3
  1. 1.Department of Electrical Engineering and Computer ScienceUniversity of MichiganAnn Arbor
  2. 2.Department of Media TechnologySogang UniversitySeoulKorea
  3. 3.Department of Nuclear Engineering and Radiological SciencesUniversity of MichiganAnn Arbor

Personalised recommendations