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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Integrating Machine Learning with Augmented Reality for Accessible Assistive Technologies

Barakat, Basel, Hall, Lynne and Keates, Simeon (2022) Integrating Machine Learning with Augmented Reality for Accessible Assistive Technologies. In: Universal Access in Human-Computer Interaction. User and Context Diversity.

Item Type: Conference or Workshop Item (Paper)


Augmented Reality (AR) is a technology which enhances physical environments by superimposing digital data on top of a real-world view. AR has multiple applications and use cases, bringing digital data into the physical world enabling experiences such as training staff on complicated machinery without the risks that come with such activities. Numerous other uses have been developed including for entertainment, with AR games and cultural experiences now emerging. Recently, AR has been used for developing assistive technologies, with applications across a range of disabilities. To achieve the high-quality interactions expected by users, there has been increasing integration of AR with Machine Learning (ML) algorithms. This integration offers additional functionality to increase the scope of AR applications. In this paper we present the potential of integrating AR with ML algorithms for developing assistive technologies, for the use case of locating objects in the home context.

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More Information

Depositing User: Basel Barakat


Item ID: 14875
Official URL:

Users with ORCIDS

ORCID for Basel Barakat: ORCID iD
ORCID for Lynne Hall: ORCID iD

Catalogue record

Date Deposited: 29 Jun 2022 15:46
Last Modified: 29 Jun 2022 15:46


Author: Basel Barakat ORCID iD
Author: Lynne Hall ORCID iD
Author: Simeon Keates

University Divisions

Faculty of Technology > School of Computer Science



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