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Motion Detection and Characterization in Videos with Cellular Automata

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Cellular Automata (ACRI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11115))

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Abstract

In this paper we present a method for motion detection and characterization using Cellular Automata. The original approach employs results of the application of the Sobel operator to individual frames, that are translated to CA configurations that are processed with the aim of detecting and characterizing moving entities to support collision avoidance from the perspective of the viewer. The paper formally describes the adopted approach as well as its experimentation videos representing plausible situations.

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Notes

  1. 1.

    https://docs.scipy.org/doc/scipy/reference/ndimage.html.

  2. 2.

    https://opencv.org/.

  3. 3.

    https://www.youtube.com/watch?v=HDb9StNG8_Q.

  4. 4.

    https://www.youtube.com/watch?v=SW3rvS3wLqg from which we digitally removed the “Ball” text.

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Authors and Affiliations

  1. Dipartimento di Informatica, Sistemistica e Comunicazione (DISCo), Universitá degli studi di Milano Bicocca, Milan, Italy

    Antonio Carrieri, Luca Crociani, Giuseppe Vizzari & Stefania Bandini

Authors
  1. Antonio Carrieri
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  2. Luca Crociani
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  3. Giuseppe Vizzari
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  4. Stefania Bandini
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Corresponding author

Correspondence to Giuseppe Vizzari .

Editor information

Editors and Affiliations

  1. University of Milano-Bicocca, Milan, Italy

    Giancarlo Mauri

  2. University of Perpignan, Perpignan, France

    Samira El Yacoubi

  3. University of Milano-Bicocca, Milan, Italy

    Alberto Dennunzio

  4. University of Tokyo, Tokyo, Japan

    Katsuhiro Nishinari

  5. University of Milano-Bicocca, Milan, Italy

    Luca Manzoni

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Carrieri, A., Crociani, L., Vizzari, G., Bandini, S. (2018). Motion Detection and Characterization in Videos with Cellular Automata. In: Mauri, G., El Yacoubi, S., Dennunzio, A., Nishinari, K., Manzoni, L. (eds) Cellular Automata. ACRI 2018. Lecture Notes in Computer Science(), vol 11115. Springer, Cham. https://doi.org/10.1007/978-3-319-99813-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-99813-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99812-1

  • Online ISBN: 978-3-319-99813-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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