Study on A Navigation System for Visually Impaired Persons based on Egocentric Vision Using Deep Learning

Sho Ooi, Takuya Okita, Mutsuo Sano
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引用次数: 2

Abstract

There are 310 thousand visually impaired persons in Japan. They use usually a white cane or a guide dog while walking. However, the number of guide dogs is less than the required number, and the white cane is difficult to get surrounding information. So, we are developing a navigation system based on egocentric vision instead of walking support tools such as a white cane. The aim of the research is to develop the navigation system with to recognize objects and estimate distances using deep learning. Therefore, to investigate to refer to landmarks object for non-handicapped persons while walking and dangerous objects for the visually impaired person. As a result, the error of the distance system for people was less than 10%, and the error of the distance system of 4-5m was less than 1m. In other words, we think that obstacle detection and distance can be presented to visually impaired people using the method proposed in this study.
基于自我中心视觉的深度学习视障人士导航系统研究
日本有31万名视障人士。他们走路时通常使用白色手杖或导盲犬。然而,导盲犬的数量少于要求的数量,白手杖很难获得周围的信息。因此,我们正在开发一种基于自我中心视觉的导航系统,而不是像白色手杖这样的行走辅助工具。本研究的目的是利用深度学习技术开发具有物体识别和距离估计功能的导航系统。因此,研究非残障人士行走时的地标性物体和视障人士行走时的危险物体。结果表明,距离系统对人的误差小于10%,4-5m距离系统的误差小于1m。换句话说,我们认为使用本研究提出的方法可以将障碍物检测和距离呈现给视障人士。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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