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Multi-Image Analysis pp 171–189Cite as

The Fusion of Image and Range Flow

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2032))

Abstract

We present quantitative results for computing local least squares and global regularized range flow using both image and range data. We first review the computation of local least squares range flow and then show how its computation can be cast in a global Horn and Schunck like regularization framework [15]. These computations are done using both range data only and using a combination of image and range data [14]. We present quantitative results for these two least squares range flow algorithms and for the two regularization range flow algorithms for one synthetic range sequence and one real range sequence, where the correct 3D motions are known a priori. We show that using both image and range data produces more accurate and more dense range flow than the use of range flow alone.

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References

  1. J. L. Barron, D. J. Fleet, and S. S. Beauchemin. Performance of optical flow techniques. IJCV, 12(1):43–77, 1994.

    Article  Google Scholar 

  2. J.L. Barron and H. Spies. Quantitative regularized range flow. In Vision Interface VI2000, pages 203–210, May 2000.

    Google Scholar 

  3. J.-A. Beraldin, S.F. El-Hakim, and F. Blais. Performance evaluation of three active vision systems built at the national research council of canada. In Conf. on Optical 3D Measurement Techniques III, pages 352–361, October 1995.

    Google Scholar 

  4. K. Chaudhury and R. Mehrota amd C. Srinivasan. Detecting 3d flow. In Proc. IEEE Int. Conf. Robotics and Automation, volume 2, pages 1073–1078, May 1994.

    Google Scholar 

  5. B. K. P. Horn and B. G. Schunck. Determining optical flow. Artificial Intelligence, 17:185–204, 1981.

    Article  Google Scholar 

  6. B.K.P. Horn and J.G. Harris. Rigid body motion from range image sequences. CVGIP: Image Understanding, 53(1):1–13, January 1991.

    Article  MATH  Google Scholar 

  7. Gregory J. Klien and Ronald H. Huesman. A 3d optical approach to addition of deformable pet volumes. In IEEE Nonrigid and Articulated Motion Workshop, pages 136–143, June 1997.

    Google Scholar 

  8. B. D. Lucas and T. Kanade. An iterative image-registration technique with an application to stereo vision. In Image Understanding Workshop, pages 121–130. DARPA, 1981. (see also IJCAI81, pp674-679).

    Google Scholar 

  9. W.H. Press, B.P. Flannery, S.A. Teukolsky, and W. T. Vetterling. Numerical Recepes in C: The art of scientific computing. Cambridge University Press, 1988.

    Google Scholar 

  10. E.P. Simoncelli. Design of multi-dimensional derivative filters. In IEEE Int. Conf. Image Processing, volume 1, pages 70–793, 1994.

    Google Scholar 

  11. S.M. Song and R.M. Leahy. Computation of 3d velocity fields from 3d cine ct images of a human heart. IEEE Trans. Medical Imaging, 10(1):295–306, 1991.

    Article  Google Scholar 

  12. S.M. Song, R.M. Leahy, D.P Boyd, and B.H. Brundage. Determining cardiac velocity fields and intraventricular pressure distribution from a sequence of ultrafast ct cardiac images. IEEE Trans. Medical Imaging, 13(2):386–397, 1994. The Fusion of Image and Range Flow 189

    Article  Google Scholar 

  13. H. Spies, H. Haußecker, B. Jahne, and J.L. Barron. Differential range flow estimation. In 21.Symposium fur Mustererkennung, DAGM’ 1999, pages 309–316. Springer, September 15-17th 1999. Bonn, Germany.

    Google Scholar 

  14. H. Spies, B. Jahne, and J.L. Barron. Dense range flow from depth and intensity data. In Int. Conf. on Pattern recognition ICPR2000, September 2000.

    Google Scholar 

  15. H. Spies, B. Jahne, and J.L. Barron. Regularised range flow. In European Conference on Computer Vision ECCV2000, June 2000.

    Google Scholar 

  16. Richard Szeliski. Estimating motion from sparse range data without correspondence. In ICCV’ 88, pages 207–216, 1988.

    Google Scholar 

  17. M. Yamamoto, P. Boulanger, J. Beraldin, and M. Rioux. Direct estimation of range flow on deformable shape from a video rate range camera. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(1):82–89, January 1993.

    Article  Google Scholar 

  18. Z. Zhou, C.E. Synolakis, R.M. Leahy, and S.M. Song. Calculation of 3d internal displacement fields from 3d x-ray computer tomographic images. Proc. R. Soc. Lond. A,449 (1937):537–554,1995

    Article  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Computer Science, University of Western Ontario, London, Ontario, Canada, N6A 5B7

    John L. Barron

  2. Interdisciplinary Center for Scientific Computing, University of Heidelberg, INF 368, 69121, Heidelberg, Germany

    Hagen Spies

Authors
  1. John L. Barron
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  2. Hagen Spies
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Editor information

Editors and Affiliations

  1. Center for image Technology and Robotics (CITR Tamaki), Auckland, New Zealand

    Reinhard Klette  & Georgy Gimel’farb  & 

  2. 2039 Beckman Institute, University of Illinois, 405 N. Mathews, Urbana, IL, 61801, USA

    Thomas Huang

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© 2001 Springer-Verlag Berlin Heidelberg

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Barron, J.L., Spies, H. (2001). The Fusion of Image and Range Flow. In: Klette, R., Gimel’farb, G., Huang, T. (eds) Multi-Image Analysis. Lecture Notes in Computer Science, vol 2032. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45134-X_13

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  • DOI: https://doi.org/10.1007/3-540-45134-X_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42122-1

  • Online ISBN: 978-3-540-45134-1

  • eBook Packages: Springer Book Archive

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