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Robust and Accurate Cylinder Triangulation

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Image Analysis (SCIA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13886))

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Abstract

In this paper we present methods for triangulation of infinite cylinders from image line silhouettes. We show numerically that linear estimation of a general quadric surface is inherently a badly posed problem. Instead we propose to constrain the conic section to a circle, and give algebraic constraints on the dual conic, that models this manifold. Using these constraints we derive a fast minimal solver based on three image silhouette lines, that can be used to bootstrap robust estimation schemes such as RANSAC. We also present a constrained least squares solver that can incorporate all available image lines for accurate estimation. The algorithms are tested on both synthetic and real data, where they are shown to give accurate results, compared to previous methods.

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Acknowledgements

This work was partially supported by the ADACORSA project with funding from ECSEL JU in the H2020 Framework Programme (H2020/2014-2020) and National Authorities, under GA 876019, and the strategic research project ELLIIT.

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Authors and Affiliations

  1. Centre for Mathematical Sciences, Lund University, Lund, Sweden

    Anna Gummeson & Magnus Oskarsson

Authors
  1. Anna Gummeson
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  2. Magnus Oskarsson
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Corresponding author

Correspondence to Anna Gummeson .

Editor information

Editors and Affiliations

  1. Aalborg University, Aalborg, Denmark

    Rikke Gade

  2. Linköping University, Linköping, Sweden

    Michael Felsberg

  3. Tampere University, Tampere, Finland

    Joni-Kristian Kämäräinen

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Gummeson, A., Oskarsson, M. (2023). Robust and Accurate Cylinder Triangulation. In: Gade, R., Felsberg, M., Kämäräinen, JK. (eds) Image Analysis. SCIA 2023. Lecture Notes in Computer Science, vol 13886. Springer, Cham. https://doi.org/10.1007/978-3-031-31438-4_30

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  • DOI: https://doi.org/10.1007/978-3-031-31438-4_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-31437-7

  • Online ISBN: 978-3-031-31438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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