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A Hidden Markov Model-Based Approach to Grasping Hand Gestures Classification

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Advances in Neural Networks (WIRN 2015)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 54))

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Abstract

Gesture recognition is a hot topic in research, due to its appealing applications in real-life contexts, from remote control to assistive robotics. In this paper we focus on grasping gestures recognition. This kind of gestures is particularly interesting, because it requires not only analyzing hand trajectories, but also fingers position and fingertip forces, of utmost importance in manipulation tasks. We used a discrete HMM-based model for gesture recognition. Input codebooks for the model are gesture elementary phases, obtained through a LLS-regression segmentation algorithm, and feature vectors representing hand position over time.

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Notes

  1. 1.

    Gesture data is heterogeneous (angles, trajectories, forces). To give an idea of algorithm results to the reader, however, we need to represent all signals on the same plot. We will omit measurement units for simplicity in this and all following figures showing hand signals.

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Authors and Affiliations

  1. Dipartimento di Ingegneria Industriale e dell’Informazione, Seconda Università degli Studi di Napoli (SUN), Aversa, Italy

    Anna Di Benedetto, Francesco A. N. Palmieri, Alberto Cavallo & Pietro Falco

Authors
  1. Anna Di Benedetto
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  2. Francesco A. N. Palmieri
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  3. Alberto Cavallo
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  4. Pietro Falco
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Corresponding author

Correspondence to Anna Di Benedetto .

Editor information

Editors and Affiliations

  1. Computer Science Department, University of Milano, Milano, Italy

    Simone Bassis

  2. Department of Psychology, Seconda Università di Napoli and IIASS, Caserta, Italy

    Anna Esposito

  3. Dept. of Info., Mathematics, Ele & Trans, Univ. Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Dip. Elettronica e Telecomunicazioni, Politecnico di Torino, Torino, Italy

    Eros Pasero

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Di Benedetto, A., Palmieri, F.A.N., Cavallo, A., Falco, P. (2016). A Hidden Markov Model-Based Approach to Grasping Hand Gestures Classification. In: Bassis, S., Esposito, A., Morabito, F., Pasero, E. (eds) Advances in Neural Networks. WIRN 2015. Smart Innovation, Systems and Technologies, vol 54. Springer, Cham. https://doi.org/10.1007/978-3-319-33747-0_41

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  • DOI: https://doi.org/10.1007/978-3-319-33747-0_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33746-3

  • Online ISBN: 978-3-319-33747-0

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