Assistive Technology for the Visually Impaired: Optimizing Frame Rate (Freshness) to Improve the Performance of Real-Time Objects Detection Application

Barakat, Basel; Steponenaite, Aiste; Lall, Gurprit S.; Arshad, Kamran; Wassell, Ian J. and Keates, Simeon. 2020. 'Assistive Technology for the Visually Impaired: Optimizing Frame Rate (Freshness) to Improve the Performance of Real-Time Objects Detection Application'. In: 22nd International Conference on Human-Computer Interaction (HCII 2020). Copenhagen, Denmark 19 - 24 July 2020. [Conference or Workshop Item]

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Abstract or Description

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:

Conference or Workshop Item (Paper)

Identification Number (DOI):

https://doi.org/10.1007/978-3-030-49108-6_34

Keywords:

Assistive Technologies, Visual Impaired, Artificial Intelligence, Machine Learning, Real-time Objects Detection, Information Freshness

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
10 July 2020Published

Event Location:

Copenhagen, Denmark

Date range:

19 - 24 July 2020

Item ID:

38186

Date Deposited:

31 Jan 2025 12:33

Last Modified:

31 Jan 2025 16:07

URI:

https://research.gold.ac.uk/id/eprint/38186

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