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Human Gesture Recognition for Elderly People Using User Training Interaction Data

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Advances in Visual Informatics (IVIC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14322))

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Abstract

Research on human-computer interaction (HCI) has been widely developed for older people. However, there needs to be more research studies on the deep learning model implementation of human gesture image data to monitor the activities of older people. There are four main stages of research, including data preparation, feature extraction using pre-trained models VGG16 and VGG19, training without and with fine-tuning, and comparing the performance of the deep learning model. This study used the dataset of Ralf Leistad Gesture with data classes as backward, forward, left, right, still, and stop. Then, the data is implemented in the data augmentation method using rotation, brightness, width shift, height shift, horizontal flip, and vertical flip. As a result of the experiment, VGG16 achieved an accuracy of 96.88%, and VGG19 reached an accuracy of 96.88%.

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Author information

Authors and Affiliations

  1. Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Selangor, Malaysia

    Nur Ani & Nazlena Mohamad Ali

  2. Faculty of Computer Science, Universitas Mercu Buana, West Jakarta, Indonesia

    Nur Ani & Vina Ayumi

Authors
  1. Nur Ani
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  2. Nazlena Mohamad Ali
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  3. Vina Ayumi
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Corresponding author

Correspondence to Nur Ani .

Editor information

Editors and Affiliations

  1. Universiti Tenaga Nasional, Kajang, Selangor, Malaysia

    Halimah Badioze Zaman

  2. University of Cambridge, Cambridge, UK

    Peter Robinson

  3. Dublin City University, Dublin, Ireland

    Alan F. Smeaton

  4. MIT Sloan School of Management, Asia School of Business, Cambridge, MA, USA

    Renato Lima De Oliveira

  5. University of Southern Denmark, Odense, Denmark

    Bo Nørregaard Jørgensen

  6. National Central University, Jhongli, Taiwan

    Timothy K. Shih

  7. Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Rabiah Abdul Kadir

  8. Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Ummul Hanan Mohamad

  9. Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

    Mohammad Nazir Ahmad

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Ani, N., Ali, N.M., Ayumi, V. (2024). Human Gesture Recognition for Elderly People Using User Training Interaction Data. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2023. Lecture Notes in Computer Science, vol 14322. Springer, Singapore. https://doi.org/10.1007/978-981-99-7339-2_10

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  • DOI: https://doi.org/10.1007/978-981-99-7339-2_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-7338-5

  • Online ISBN: 978-981-99-7339-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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