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Mobile Augmented Reality using 5G: A trial at the Roman Baths in the 5G Smart Tourism project

White Paper WHP 348

Published: 10 September 2019

Abstract

Modern mobile devices offer significant possibilities for providing rich AR and VR content, although this generally requires a large quantity of data, particularly where high-resolution 360-degree videos or highly-detailed animations are involved. This limits what is possible, particularly for users who are on a mobile network. The emergence of 5G technology presents a potential solution.

This White Paper summarises the technical developments and trials carried out by ±«Óãtv Research & Development at the Roman Baths in Bath, in the 5G Smart Tourism project in 2018-19. The work involved developing a mobile app that presented views of animated historical reconstructions of the baths at various points in time, using the so-called ‘magic window’ paradigm where the user moves their device around to see a view as if they were looking through the screen. The views were rendered to align with the user’s actual position and orientation. Two technical approaches were investigated: streaming of pre-rendered 360-degree video (allowing the user to change device orientation), and streaming video rendered in real-time on a remote server (allowing the user to change both position and orientation). This document includes an overview of the mobile app that was developed, discusses the user trials, and presents an analysis of the technical and user survey data. Some insights into future use cases and business models are also included.

The work was conducted in collaboration with the team at the baths, and , who were contracted to develop the content. Other project partners were involved in providing the trial network. This document is based on deliverable WP3-D1 from the , and extends the material in the paper A. Murphy, B. Weir, M. Waddell, R. Khokhar. "", IBC, September 2019.

White Paper copyright

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The ±«Óãtv grants permission to individuals and organisations to make copies of any White Paper as a complete document (including the copyright notice) for their own internal use. No copies may be published, distributed or made available to third parties whether by paper, electronic or other means without the ±«Óãtv's prior written permission.

Authors

  • Graham Thomas (MA PhD CEng FIET)

    Graham Thomas (MA PhD CEng FIET)

    Head of Applied Research, Production
  • Todd Burlington

    Graduate R&D Engineer
  • Hannah Clawson (MSc)

    Hannah Clawson (MSc)

    Research & Development Graduate Engineer, Psychology
  • James Gibson

    Trainee Research Technologist
  • Maxine Glancy (BA, MA, MPhil, BSc)

    Senior Research Scientist
  • Alia Sheikh

    Alia Sheikh

    Senior Development Producer
  • Bruce Weir (PhD)

    Bruce Weir (PhD)

    Senior Engineer

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