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Indoor Navigation Aid Systems for the Blind and Visually Impaired Based on Depth Sensors

Indoor Navigation Aid Systems for the Blind and Visually Impaired Based on Depth Sensors

Fernando Merchan, Martin Poveda, Danilo E. Cáceres-Hernández, Javier E. Sanchez-Galan
Copyright: © 2021 |Pages: 37
ISBN13: 9781799865223|ISBN10: 1799865223|ISBN13 Softcover: 9781799865230|EISBN13: 9781799865247
DOI: 10.4018/978-1-7998-6522-3.ch007
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MLA

Merchan, Fernando, et al. "Indoor Navigation Aid Systems for the Blind and Visually Impaired Based on Depth Sensors." Examining Optoelectronics in Machine Vision and Applications in Industry 4.0, edited by Oleg Sergiyenko, et al., IGI Global, 2021, pp. 187-223. https://doi.org/10.4018/978-1-7998-6522-3.ch007

APA

Merchan, F., Poveda, M., Cáceres-Hernández, D. E., & Sanchez-Galan, J. E. (2021). Indoor Navigation Aid Systems for the Blind and Visually Impaired Based on Depth Sensors. In O. Sergiyenko, J. Rodriguez-Quiñonez, & W. Flores-Fuentes (Eds.), Examining Optoelectronics in Machine Vision and Applications in Industry 4.0 (pp. 187-223). IGI Global. https://doi.org/10.4018/978-1-7998-6522-3.ch007

Chicago

Merchan, Fernando, et al. "Indoor Navigation Aid Systems for the Blind and Visually Impaired Based on Depth Sensors." In Examining Optoelectronics in Machine Vision and Applications in Industry 4.0, edited by Oleg Sergiyenko, Julio C. Rodriguez-Quiñonez, and Wendy Flores-Fuentes, 187-223. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-6522-3.ch007

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Abstract

This chapter focuses on the contributions made in the development of assistive technologies for the navigation of blind and visually impaired (BVI) individuals. A special interest is placed on vision-based systems that make use of image (RGB) and depth (D) information to assist their indoor navigation. Many commercial RGB-D cameras exist on the market, but for many years the Microsoft Kinect has been used as a tool for research in this field. Therefore, first-hand experience and advances on the use of Kinect for the development of an indoor navigation aid system for BVI individuals is presented. Limitations that can be encountered in building such a system are addressed at length. Finally, an overview of novel avenues of research in indoor navigation for BVI individuals such as integration of computer vision algorithms, deep learning for the classification of objects, and recent developments with stereo depth vision are discussed.

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