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Details of Grant 

EPSRC Reference: EP/T03324X/1
Title: EPSRC-SFI: SpheryStream
Principal Investigator: TONI, Dr L
Other Investigators:
Researcher Co-Investigators:
Project Partners:
BBC Nat Inst for Maths & Computer Sci (CWI) Ozyegin University
Trinity College Dublin
Department: Electronic and Electrical Engineering
Organisation: UCL
Scheme: Standard Research
Starts: 01 August 2020 Ends: 31 July 2022 Value (£): 257,481
EPSRC Research Topic Classifications:
Artificial Intelligence Computer Graphics & Visual.
Human-Computer Interactions Image & Vision Computing
EPSRC Industrial Sector Classifications:
Communications Information Technologies
Creative Industries
Related Grants:
Panel History:
Panel DatePanel NameOutcome
20 May 2020 EPSRC ICT Prioritisation Panel May 2020 Announced
Summary on Grant Application Form
This proposal addresses the important and not well-studied area in the fast-developing engineering space of the virtual reality and immersive technology. Our final vision is to endow any final user with an unprecedented sense of full immersion in virtual environments for any applicative scenario and with any connectivity level. This requires VR systems that operate at scale, in a personalized manner, remaining bandwidth-tolerant whilst meeting quality and latency criteria. This can be accomplished only by a fundamental revolution of the coding/streaming/rendering chain that has to put the interactive user at the heart of the system rather than at the end of the chain.

Specifically, bringing our final vision to reality requires constant innovation in VR streaming technology to overcome the following main challenges: i) the spherical format of the video content in a scenario in which media codecs are optimized for planar content; ii) the interactive behaviour of users that introduces uncertainty on the popularity of the video content. To overcome the former challenges, the spherical video is currently projected on a bidimensional planar domain, but this introduces noticeable deformation since the sphere is not a developable surface. To address the uncertainty of users' behaviours, predicting models have been investigated recently, but none of them actually work on the spherical (not deformed) domain.

To overcome the above challenges in immersive technology, there is the need to develop an efficient tool for navigation patterns analysis in the spherical domain and leverage on that to predict users' behaviour and build the entire coding-delivery-rendering pipeline as a user- and geometry-centric system. This proposal focuses on develop novel VR delivery strategies, which will rely on the analysis and prediction of the navigation patterns of the omnidirectional content navigation, in a user, content- and application-dependent fashion. Predicting users' behaviour will allow to delivery only the content that will be actually consumed by the users, minimising the transmission resources consumption while maximising the user's Quality of Experience. The key novelty will be to address the above challenges working directly on the spherical domain, rather than on the projected (thus deformed) bidimensional domain. The developed VR system will be tested via a real omnidirectional video streaming testbed that will be implemented within the scope of the project. The outcomes of the project will be three-folds: i) user- content- and application-dependent VR streaming platform, optimized from the source codec to the delivery platform; ii) users analysis tools able to assess users' behaviour (when interactive with the content) in an objective fashion to identify common navigation patterns, and to predict future behaviours; iii) VR streaming testbed to test the proposed technology.

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