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Signatures in Shape Analysis: An Efficient Approach to Motion Identification

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Geometric Science of Information (GSI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11712))

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Abstract

Signatures provide a succinct description of certain features of paths in a reparametrization invariant way. We propose a method for classifying shapes based on signatures, and compare it to current approaches based on the SRV transform and dynamic programming.

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Notes

  1. 1.

    A more thorough analysis of the run time complexities associated with these algorithms has been left out due to space constraints.

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Acknowledgements

This paper contains work done as part of P.E.L.’s master thesis. The master thesis will be published separately as part of NTNU’s Master of Science program in Applied Physics and Mathematics [12]. N.T. acknowledges that part of this work was carried out during his tenure of an ERCIM ‘Alain Bensoussan’ Fellowship Programme. This work was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie, grant agreement No.691070.

The data used in this project was obtained from http://mocap.cs.cmu.edu. The database was created with funding from NSF EIA-0196217.

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Authors and Affiliations

  1. Department of Mathematical Sciences, NTNU Trondheim, Trondheim, Norway

    Elena Celledoni, Pål Erik Lystad & Nikolas Tapia

Authors
  1. Elena Celledoni
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  2. Pål Erik Lystad
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  3. Nikolas Tapia
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Corresponding author

Correspondence to Nikolas Tapia .

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Editors and Affiliations

  1. Sony Computer Science Laboratories, Inc., Tokyo, Japan

    Frank Nielsen

  2. Thales, Limours, France

    Frédéric Barbaresco

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Celledoni, E., Lystad, P.E., Tapia, N. (2019). Signatures in Shape Analysis: An Efficient Approach to Motion Identification. In: Nielsen, F., Barbaresco, F. (eds) Geometric Science of Information. GSI 2019. Lecture Notes in Computer Science(), vol 11712. Springer, Cham. https://doi.org/10.1007/978-3-030-26980-7_3

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  • DOI: https://doi.org/10.1007/978-3-030-26980-7_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26979-1

  • Online ISBN: 978-3-030-26980-7

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