2022
DOI: 10.3390/app12062802
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A Smartphone-Based Mobility Assistant Using Depth Imaging for Visually Impaired and Blind

Abstract: The means of assisting visually impaired and blind (VIB) people when travelling usually relies on other people. Assistive devices have been developed to assist in blind navigation, but many technologies require users to purchase more devices and they lack flexibility, thus making it inconvenient for VIB users. In this research, we made use of a mobile phone with a depth camera function for obstacle avoidance and object recognition. It includes a mobile application that is controlled using simple voice and gest… Show more

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Cited by 30 publications
(13 citation statements)
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“…The author of [14,15] describes a successful mobile application for mobility aid that gives users access to a portable, adaptable navigational assistive device that combines object detection and obstacle detection. It can be operated with gestures and a voicecommand-enabled user interface.…”
Section: Background and Related Workmentioning
confidence: 99%
“…The author of [14,15] describes a successful mobile application for mobility aid that gives users access to a portable, adaptable navigational assistive device that combines object detection and obstacle detection. It can be operated with gestures and a voicecommand-enabled user interface.…”
Section: Background and Related Workmentioning
confidence: 99%
“…According to the opinion of some visually impaired individuals, their major problem is to locate a place precisely [4]. Assisting the visually impaired and blind persons when moving from one place to another usually relies on other persons [15]. Visual impairment (VI) is a condition of reduced visual function that cannot be improved by the use of glasses, surgery or other medical methods.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Visual information of the environment is also used to detect and localise nearby obstacles by applying deep-learning methods [ 25 ]. Recently, the improved hardware performance coupled with an efficient deep learning architecture designed for mobile implementation [ 29 , 30 ] allowed for real-time execution with low power consumption. In addition, the semantic information of an object such as this nature improves the understanding of the degree of danger that this object represents.…”
Section: Related Workmentioning
confidence: 99%