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Quasi-Invariant Parameterisations and Their Applications in Computer Vision

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Shape, Contour and Grouping in Computer Vision

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1681))

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Abstract

In this paper, we show that there exist quasi-invariant pa- rameterisations which are not exactly invariant but approximately invari- ant under group transformations and do not require high order deriva- tives. The affine quasi-invariant parameterisation is investigated in more detail and exploited for defining general affine semi-local invariants from second order derivatives only. The new invariants are implemented and used for matching curve segments under general affine motions and ex- tracting symmetry axes of objects with 3D bilateral symmetry.

The authors acknowledge the support of the EPSRC, grant GR/K84202

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Authors and Affiliations

  1. Nagoya Institute of Technology, Nagoya, 466, Japan

    Jun Sato

  2. Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, UK

    Jun Sato & Roberto Cipolla

Authors
  1. Jun Sato
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  2. Roberto Cipolla
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© 1999 Springer-Verlag Berlin Heidelberg

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Sato, J., Cipolla, R. (1999). Quasi-Invariant Parameterisations and Their Applications in Computer Vision. In: Shape, Contour and Grouping in Computer Vision. Lecture Notes in Computer Science, vol 1681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46805-6_6

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  • DOI: https://doi.org/10.1007/3-540-46805-6_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66722-3

  • Online ISBN: 978-3-540-46805-9

  • eBook Packages: Springer Book Archive

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