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Computer Vision Techniques for Hand Gesture Recognition: Survey

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New Trends in Information and Communications Technology Applications (NTICT 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1764))

Abstract

Hand gesture recognition has recently emerged as a critical component of the human-computer interaction (HCI) concept, allowing computers to capture and interpret hand gestures. In addition to their use in many medical applications, communication between the hearing impaired, device automation, and robot control, hand gestures are of particular importance as a form of nonverbal communication. So far, hand gesture recognition has taken two approaches and relied on a variety of technologies; the first on sensor technology and the second on computer vision. Given the importance of hand gesture recognition applications and technology development today, the importance of the research lies in shedding light on the latest techniques used in the recognition and interpretation of hand gestures. A survey on the techniques used from 2017–2022 has been presented in this research, with a focus on the computer vision approach. The survey was carried out as follows: the first part dealt with research based on artificial intelligence techniques for hand gesture recognition, and the second part focused on research that used artificial neural networks and deep learning for hand gesture recognition.

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  1. Software Department, University of Babylon, Babylon, Iraq

    Noor Fadel

  2. Computer Science Department, Mustansiriyah University, Baghdad, Iraq

    Emad I. Abdul Kareem

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  1. Noor Fadel
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  1. University of Information Technology and Communications, Baghdad, Iraq

    Abbas M. Al-Bakry

  2. University of Information Technology and Communications, Baghdad, Iraq

    Safaa O. Al-Mamory

  3. University of Information Technology and Communications, Baghdad, Iraq

    Mouayad A. Sahib

  4. University of Information Technology and Communications, Baghdad, Iraq

    Loay E. George

  5. University of Information Technology and Communications, Baghdad, Iraq

    Jaafar A. Aldhaibani

  6. University of Information Technology and Communications, Baghdad, Iraq

    Haitham S. Hasan

  7. Open University of Tanzania, Dar es Salaam, Tanzania

    George S. Oreku

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Fadel, N., Kareem, E.I.A. (2023). Computer Vision Techniques for Hand Gesture Recognition: Survey. In: Al-Bakry, A.M., et al. New Trends in Information and Communications Technology Applications. NTICT 2022. Communications in Computer and Information Science, vol 1764. Springer, Cham. https://doi.org/10.1007/978-3-031-35442-7_4

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