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Subpixel Flow Detection by the Hough Transform

  • Atsushi Imiya
  • Keisuke Iwawaki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1998)

Abstract

In this paper, we show that randomized sampling and voting processes allow to treat linear flow field detection as a model-fitting problem. If we use an appropriate number of images from a sequence of images, it is possible to detect subpixel motion in this sequence. We use the accumulator space for the unification of these flow vectors which are computed from different time intervals.

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References

  1. 1.
    A. Imiya, I. Fermin: Voting method for planarity and motion detection. Image and Vision Computing, 17 (1999) 867–879. 140CrossRefGoogle Scholar
  2. 2.
    A. Imiya, I. Fermin: Motion analysis by random sampling and voting process. Computer Vision and Image Understanding, 73 (1999) 309–328. 140zbMATHCrossRefGoogle Scholar
  3. 3.
    E. Oja, L. Xu, P. Kultanen: Curve detection by an extended self-organization map and related RHT method. Proceed. Internat. on Neural Network Conf., 1 (1990) 27–30. 140Google Scholar
  4. 4.
    H. Kälviäinen, E. Oja, L. Xu: Randomized Hough transform applied to translation and rotation motion analysis. 11th IAPR Proceed. of Internat. Conf. on Pattern Recognition (1992) 672–675. 140Google Scholar
  5. 5.
    J. Heikkonen: Recovering 3-D motion parameters from optical flow field using randomized Hough transform. Pattern Recognition Letters, 15 (1995) 971–978. 140CrossRefGoogle Scholar
  6. 6.
    K. Kanatani: Statistical optimization and geometric inference in computer vision, Philosopical Transactions of the Royal Society of London, Series A, 356 (1997) 1308–1320.Google Scholar
  7. 7.
    C. R. Rao, S. K. Mitra: Generalized Inverse of Matrices and its Applications. John Wiley & Sons, New York, (1971). (Japanese Edition: Tokyo Tosho, Tokyo (1973)). 141zbMATHGoogle Scholar
  8. 8.
    J. L. Barron, D. J. Fleet, S. S. Beauchemin: Performance of optical flow techniques. Report No. 299, Department of Computer Science, The University of Western Ontario, London (1992). 142, 145Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Atsushi Imiya
    • 1
  • Keisuke Iwawaki
    • 1
  1. 1.Computer Science Division, Dept. of Information and Image SciencesChiba UniversityChibaJapan

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