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Identification of Visually Impaired Person with Deep Learning

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Intelligent Human Systems Integration (IHSI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 722))

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Abstract

The purpose of this study is to identify visually impaired persons by analyzing still pictures of walking of a visually impaired person and that of a healthy person using deep learning. Still images of walking are taking still pictures from video images. Shoot from sideways and diagonally with two video cameras. The number of images (with 1000 or 2000) and the dropout (three, two, or one time) was changed and analyzed. Because the study focused on only visually impaired persons (totally blind persons) and the healthy person’s study machines of two patterns in the experiment, a correct answer rate of 99.9% for every 2000 images and 2 times of the dropout number was obtained.

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Authors and Affiliations

  1. Tokushima University, Institute of Technology and Science, 2-1 Minamijosan-jima, Tokushima, Tokushima, 770-8506, Japan

    Shoichiro Fujisawa, Ranmaru Mandai, Shin-ichi Ito & Katsuya Sato

  2. Kobe City College of Technology, 8-3 Gakuenhigashi, Nishi-ku, Kobe, Hogo, Japan

    Ryota Kurozumi

Authors
  1. Shoichiro Fujisawa
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  2. Ranmaru Mandai
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  3. Ryota Kurozumi
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  4. Shin-ichi Ito
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  5. Katsuya Sato
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Corresponding author

Correspondence to Shoichiro Fujisawa .

Editor information

Editors and Affiliations

  1. University of Central Florida, Orlando, Florida, USA

    Waldemar Karwowski

  2. University of Central Florida, Orlando, Florida, USA

    Tareq Ahram

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Fujisawa, S., Mandai, R., Kurozumi, R., Ito, Si., Sato, K. (2018). Identification of Visually Impaired Person with Deep Learning. In: Karwowski, W., Ahram, T. (eds) Intelligent Human Systems Integration. IHSI 2018. Advances in Intelligent Systems and Computing, vol 722. Springer, Cham. https://doi.org/10.1007/978-3-319-73888-8_93

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  • DOI: https://doi.org/10.1007/978-3-319-73888-8_93

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73887-1

  • Online ISBN: 978-3-319-73888-8

  • eBook Packages: EngineeringEngineering (R0)

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