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Using Neural Factorization of Shape and Reflectance for Ball Detection

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RoboCup 2023: Robot World Cup XXVI (RoboCup 2023)

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Abstract

Visually detecting a well-defined object like a soccer ball should be a simple problem. Under good lighting conditions this problem can be claimed to be solved, but unfortunately, the lighting conditions are not always optimal. In those circumstances, it is valuable to have a shape and reflectance model of the ball, to be able to predict how its appearance changes if the lighting changes. This is a prerequisite for playing soccer outside, with direct sunlight and clouds. The predicted appearance will be used to fine-tune an existing ball detection algorithm, based on the classic Yolo algorithm.

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Notes

  1. 1.

    https://www.intelligentroboticslab.nl/.

  2. 2.

    https://spl.robocup.org/.

  3. 3.

    https://github.com/AlexeyAB, maintained by Alexey Bochkovsky.

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Authors and Affiliations

  1. Intelligent Robotics Lab, Universiteit van Amsterdam, Amsterdam, The Netherlands

    Xavier Monté, Joey van der Kaaij, Rogier van der Weerd & Arnoud Visser

Authors
  1. Xavier Monté
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  2. Joey van der Kaaij
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  3. Rogier van der Weerd
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  4. Arnoud Visser
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Corresponding author

Correspondence to Arnoud Visser .

Editor information

Editors and Affiliations

  1. ENIB/Naval Group Pacific, Plouzané, France

    Cédric Buche

  2. University of Naples Federico II, Naples, Italy

    Alessandra Rossi

  3. Bahia State University, Salvador, Brazil

    Marco Simões

  4. University of Miami, Coral Gables, FL, USA

    Ubbo Visser

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Monté, X., van der Kaaij, J., van der Weerd, R., Visser, A. (2024). Using Neural Factorization of Shape and Reflectance for Ball Detection. In: Buche, C., Rossi, A., Simões, M., Visser, U. (eds) RoboCup 2023: Robot World Cup XXVI. RoboCup 2023. Lecture Notes in Computer Science(), vol 14140. Springer, Cham. https://doi.org/10.1007/978-3-031-55015-7_11

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  • DOI: https://doi.org/10.1007/978-3-031-55015-7_11

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