BMVC91 pp 160-168 | Cite as

Optimal Surface Fusion

  • Peter R. J. North
Conference paper

Abstract

This paper presents a general method for combining stereo surfaces using a Kalman filter. A measure of error in surface representation is suggested, and the work shows how a set of surfaces may be combined to give a single surface which minimises this measure. The analysis shows how a stochastic surface may be generated using stereo, and how errors in surface-to-surface registration may be modeled. The cases of multiple, mutually-occluding surfaces and unknown three-dimensional camera motion are considered. Performance is analysed using semi-artificial data. The results are important to multi-sensor fusion and automatic model generation.

Keywords

Covariance Autocorrelation 

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References

  1. [1]
    Ayache, N. and Faugeras, O.D. Building, registrating and fusing noisy visual maps. First Int. Conf. on Computer Vision, pages 73-82, 1987.Google Scholar
  2. [2]
    Durrant-Whyte, H.F. Integration, Coordination and Control of Multi-Sensor Robot Systems. Kluwer Academic Publishers, 1988.Google Scholar
  3. [3]
    Terzopoulos, D. Integrating visual information from multiple sources. In A.P. Pentland, editor, From Pixels to Predicates. Ablex Press, 1986.Google Scholar
  4. [4]
    Grant, P. and Mowforth, P. Economical and cautions approaches to local path planning for a mobile robot. Proc. of the AVC, Reading, pages 297-300, 1989.Google Scholar
  5. [5]
    North, P.R.J. Reconstruction of visual appearance. Proc. of the BMVC, pages 205-210, 1990.Google Scholar
  6. [6]
    Nishihara, H. K. Practical real-time imaging stereo matcher. Optical Engineering, 23(5):536–545, 1984.MathSciNetGoogle Scholar
  7. [7]
    Matthies, L., Kanade, T., and Szeliski, R. Kalman filter-based algorithms for estimating depth from image sequences. Int. Journal of Computer Vision IJCV, 3(3):209–238, 1989.CrossRefGoogle Scholar
  8. [8]
    North, P.R.J. Visual model generation by combiningstereo surfaces. CSRP 192, School of COGS, University of Sussex, 1991.Google Scholar
  9. [9]
    Charnley, D. and Blissett, R. Surface reconstruction from outdoor image sequences. Proc. of the AVC, Manchester, pages 153-158, 1988.Google Scholar
  10. [10]
    Brav, A.J. Tracking curved objects by perspective inversion. Proc. of the BMVC, 1991.Google Scholar
  11. [11]
    Grossman, P. COMPACT — a. surface representation scheme. Proc. of the AVC Manchester, pages 97-102, 1988.Google Scholar
  12. [12]
    Connolly, C. I. Cumulative generation of octree models from range data. Proc. of the Int. Conf on Robotics, pages 25-32, 1984.Google Scholar

Copyright information

© Springer-Verlag London Limited 1991

Authors and Affiliations

  • Peter R. J. North
    • 1
  1. 1.School of Cognitive and Computing SciencesUniversity of SussexUK

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