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SwarmCurves: Evolutionary Curve Reconstruction

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Advances in Visual Computing (ISVC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14361))

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Abstract

The problem of recovering the shape of a curve given partial information about it is a fundamental problem in many applications in visual computing. Which types of curves are fitted to a given input data depends on the application and varies from piece-wise linear approximation to parametric splines. The choice of approximation method depends on the context of the problem, the nature of the data, and the desired level of accuracy and complexity.

In this paper we introduce SwarmCurves, a curve reconstruction approach based on particle swarm optimization. For given input data SwarmCurves  offers a range of solutions, from linear polygons to rational B-Splines with various degrees of freedom. The algorithm works on dense, sparse or noisy, 2D or 3D input data. We demonstrate the performance of SwarmCurves, on a number of examples.

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Authors and Affiliations

  1. Institute of Computer Graphics and Knowledge Visualisation, Graz University of Technology, Graz, Austria

    Alexander Komar & Ursula Augsdörfer

Authors
  1. Alexander Komar
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  2. Ursula Augsdörfer
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Corresponding author

Correspondence to Alexander Komar .

Editor information

Editors and Affiliations

  1. University of Nevada Reno, Reno, NV, USA

    George Bebis

  2. Google Research, Mountain View, CA, USA

    Golnaz Ghiasi

  3. New York University, New York, USA

    Yi Fang

  4. Ben-Gurion University, Be'er Sheva, Israel

    Andrei Sharf

  5. Microsoft Research, Beijing, China

    Yue Dong

  6. The University of Oklahoma, Norman, OK, USA

    Chris Weaver

  7. University of Maryland, Collage Park, MD, USA

    Zhicheng Leo

  8. University of Central Florida, Orlando, FL, USA

    Joseph J. LaViola Jr.

  9. InnerOptic Technology, Hillsborough, NC, USA

    Luv Kohli

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Komar, A., Augsdörfer, U. (2023). SwarmCurves: Evolutionary Curve Reconstruction. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2023. Lecture Notes in Computer Science, vol 14361. Springer, Cham. https://doi.org/10.1007/978-3-031-47969-4_27

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  • DOI: https://doi.org/10.1007/978-3-031-47969-4_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-47968-7

  • Online ISBN: 978-3-031-47969-4

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