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International Conference on Hybrid Artificial Intelligence Systems

HAIS 2020: Hybrid Artificial Intelligent Systems pp 561–572Cite as

A Real Time Vision System Based on Deep Learning for Gesture Based Human Machine Interaction

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12344))

Abstract

The use of gestures is one of the principal ways of communication among human beings when other forms, such as speech, are not possible. Taking this as a basis, the use of gestures has become also a principal form of human machine interaction in many different fields, ranging from advanced industrial setups where robots are commanded by gestures, to the use of hands to remotely control multimedia devices present at home.

The majority of the systems for gesture detection are based on computer vision, either color images, depth images or point clouds, and have to overcome the inherent problems of image processing: light variations, occlusions or change of color. To overcome all these problems, recent developments using deep learning techniques have been presented, using Convolutional Neural Networks.

This work presents a hand gesture recognition system based on Convolutional Neural Networks and RGB images that is robust against environmental variations, fast enough to be considered real time in embedded interaction applications, and that overcomes the principal drawbacks of the state of the art hand gesture recognition systems presented in previous works.

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Author information

Authors and Affiliations

  1. D4K Group, University of Deusto, Avda. Universidades 24, 48007, Bilbao, Spain

    Alberto Tellaeche Iglesias, Iker Pastor-López, Borja Sanz Urquijo & Pablo García-Bringas

Authors
  1. Alberto Tellaeche Iglesias
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  2. Iker Pastor-López
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  3. Borja Sanz Urquijo
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  4. Pablo García-Bringas
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Corresponding author

Correspondence to Alberto Tellaeche Iglesias .

Editor information

Editors and Affiliations

  1. University of Oviedo, Oviedo, Spain

    Enrique Antonio de la Cal

  2. University of Oviedo, Oviedo, Spain

    José Ramón Villar Flecha

  3. University of A Coruña, Ferrol, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Tellaeche Iglesias, A., Pastor-López, I., Sanz Urquijo, B., García-Bringas, P. (2020). A Real Time Vision System Based on Deep Learning for Gesture Based Human Machine Interaction. In: de la Cal, E.A., Villar Flecha, J.R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2020. Lecture Notes in Computer Science(), vol 12344. Springer, Cham. https://doi.org/10.1007/978-3-030-61705-9_46

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  • DOI: https://doi.org/10.1007/978-3-030-61705-9_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61704-2

  • Online ISBN: 978-3-030-61705-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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