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Stairway Detection Based on Single Camera by Motion Stereo for the Blind and Visually Impaired

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Machine Vision and Navigation

Abstract

This chapter presents a method to solve the stairway localization and recognition problem for both indoor and outdoor cases by using a convolutional neural network technique. To blind and visually impaired persons, these assistive technology application has an important impact on their daily life. The algorithm should be able to solve the problem of stair classification for both cases, indoor and outdoor scenes. The proposed idea describes the strategy for introducing an affordable method that can recognize stairways without taking into account the environments. First, this method uses stair features to classify images by using convolutional neural networks. Second, stairway candidate is extracted by using the Gabor filter a linear filter. Third, the set of lines that belong to the ground plane are removed by using the behavioral distance measurement between two consecutive frames. Finally, from this step, we extract the tread depth and the riser height of the stairways.

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Abbreviations

BLS:

Bottommost line segments

CCD:

Charge-coupled device

CNN:

Convolutional neural networks

HH:

Horizontal histogram

ILSVRC2012:

Large Scale Visual Recognition Challenge 2012

KNN:

K-nearest neighbors

MDPG:

Maximum distance of plane ground

PA:

Candidate area

PE:

Number of areas

PL:

Number of lines

PP:

Number of pixels

SVM:

Support vector machines

vAOV:

Vertical angle of view

VH:

Vertical histogram

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Acknowledgments

The authors would like to thank the National Bureau of Science, Technology and Innovation of Panama (SENACYT), the Sistema Nacional de Investigación (SNI) of Panama (SNI Contract 168-2017 and SNI Contract 129-2018), and the Universidad Tecnológica de Panamá for their administrative support and contribution.

Author information

Authors and Affiliations

  1. Grupo de Investigación en Biotecnología, Bioinformática y Biología de Sistemas, Centro de Producción e Investigaciones Agroindustriales (CEPIA), Universidad Tecnológica de Panamá, Panama, Republic of Panama

    Javier E. Sanchez-Galan

  2. Institute of Advanced Scientific Research and High Technology, Panama, Republic of Panama

    Javier E. Sanchez-Galan

  3. Intelligent Systems Laboratory, Graduate School of Electrical Engineering, University of Ulsan, Ulsan, South Korea

    Kang-Hyun Jo

  4. Grupo de Sistemas Inteligentes, Facultad de Ingeniería Eléctrica, Universidad Tecnológica de Panamá, Panamá, Republic of Panama

    Danilo Cáceres-Hernández

Authors
  1. Javier E. Sanchez-Galan
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  2. Kang-Hyun Jo
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  3. Danilo Cáceres-Hernández
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Corresponding author

Correspondence to Danilo Cáceres-Hernández .

Editor information

Editors and Affiliations

  1. Universidad Autónoma de Baja California, Mexicali, Baja California, Mexico

    Oleg Sergiyenko

  2. Universidad Autónoma de Baja California, Mexicali, Baja California, Mexico

    Wendy Flores-Fuentes

  3. Leuphana University of Lueneburg, Lueneburg, Low Saxony, Niedersachsen, Germany

    Paolo Mercorelli

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Sanchez-Galan, J.E., Jo, KH., Cáceres-Hernández, D. (2020). Stairway Detection Based on Single Camera by Motion Stereo for the Blind and Visually Impaired. In: Sergiyenko, O., Flores-Fuentes, W., Mercorelli, P. (eds) Machine Vision and Navigation. Springer, Cham. https://doi.org/10.1007/978-3-030-22587-2_20

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  • DOI: https://doi.org/10.1007/978-3-030-22587-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22586-5

  • Online ISBN: 978-3-030-22587-2

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