Barakat, Basel ORCID: 0000-0001-9126-7613, Steponenaite, Aiste, Lall, Gurprit S., Arshad, Kamran, Wassell, Ian J. and Keates, Simeon ORCID: 0000-0002-2826-672X (2020) Assistive technology for the visually impaired: Optimizing frame rate (freshness) to improve the performance of real-time objects detection application. In: Antona, Margherita and Stephanidis, Constantine, (eds.) Universal Access in Human-Computer Interaction. Applications and Practice. Lecture Notes in Computer Science (LNCS) (12189). Springer Nature, Switzerland, pp. 479-492. ISBN 978-3030491079 (doi:https://doi.org/10.1007/978-3-030-49108-6_34)

PDF (Author Accepted Book Chapter) 28391 LALL_Assistive_Technology_for_the_Visually_Impaired_2020.pdf - Accepted Version Restricted to Registered users only Download (2MB) | Request a copy

Abstract

It has been 100+ years since the world's first commercial radio station started. This century witnessed several astonishing inventions (e.g. the computer, internet and mobiles) that have shaped the way we work and socialize. With the start of a new decade, it is evident that we are becoming more reliant on these new technologies as the majority of the world population relies on the new technology on a daily basis. As world’s population is becoming reliant on new technologies and we are shaping our lives around it, it is of paramount importance to consider those people who struggle in using the new technologies and inventions. In this paper, we are presenting an algorithm and a framework that helps partially sighted people to locate their essential belongings. The framework integrates state-of-the-art technologies from computer vision, speech recognition and communication queueing theory to create a framework that can be implemented on low computing power platforms. The framework verbally communicates with the users to identify the object they are aiming to find and then notify them when it is within the range.

Item Type:	Book Section
Additional Information:	14th International Conference, UAHCI 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part II
Uncontrolled Keywords:	Assistive Technologies, Visual Impaired, Artificial Intelligence, Machine Learning, Real-time Objects Detection, Information Freshness.
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > Medway School of Pharmacy
Last Modified:	24 Nov 2020 17:25
URI:	http://gala.gre.ac.uk/id/eprint/28391

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