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3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition

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Multi-faceted Deep Learning

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Abstract

3D convolutional networks is a good means to perform tasks such as video segmentation into coherent spatio-temporal chunks and classification of them with regard to a target taxonomy. In the chapter we are interested in the classification of continuous video takes with repeatable actions, such as strokes of table tennis. Filmed in a free marker less ecological environment, these videos represent a challenge from both segmentation and classification point of view. The 3D convnets are an efficient tool for solving these problems with window-based approaches.

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Notes

  1. 1.

    https://www.mturk.com/.

  2. 2.

    https://www.csc.kth.se/cvap/actions/.

  3. 3.

    http://www.wisdom.weizmann.ac.il/~vision/SpaceTimeActions.html.

  4. 4.

    https://www.cvssp.org/acasva/Downloads.html.

  5. 5.

    https://sdolivia.github.io/FineGym/.

  6. 6.

    https://www.di.ens.fr/~laptev/actions/hollywood2/.

  7. 7.

    www.crcv.ucf.edu/data/UCF_YouTube_Action.php.

  8. 8.

    www.crcv.ucf.edu/data/UCF101.php.

  9. 9.

    www.thumos.info.

  10. 10.

    https://deepmind.com/research/open-source/kinetics.

  11. 11.

    https://research.google.com/ava/.

  12. 12.

    https://deepmind.com/research/open-source/kinetics.

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Authors and Affiliations

  1. Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

    Pierre-Etienne Martin

  2. LaBRI UMR 5800, University of Bordeaux, Talence Cedex, France

    Jenny Benois-Pineau & Akka Zemmari

  3. MIA, University of La Rochelle, La Rochelle, France

    Renaud Péteri

  4. IMS, University of Bordeaux, Talence Cedex, France

    Julien Morlier

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  1. LaBRI UMR 5800, University of Bordeaux, Talence Cedex, France

    Jenny Benois-Pineau

  2. LaBRI UMR 5800, University of Bordeaux, Talence Cedex, France

    Akka Zemmari

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Martin, PE., Benois-Pineau, J., Péteri, R., Zemmari, A., Morlier, J. (2021). 3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition. In: Benois-Pineau, J., Zemmari, A. (eds) Multi-faceted Deep Learning. Springer, Cham. https://doi.org/10.1007/978-3-030-74478-6_9

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