The BBC is building a system that could turn a single TV programme into millions of different versions, each tailored to one viewer. Today, watching a football match means seeing the same camera angles and commentary as everyone else. This project aims to let each viewer choose their own view of the pitch, their preferred commentator, or even have graphics appear in their native language—all delivered in real time over the internet. The core problem is scale. Current streaming services can recommend different shows, but they cannot adapt the content itself for millions of people simultaneously. To do that, the researchers must solve three linked challenges: automatically breaking video into separate objects (players, crowd, graphics), creating tools for producers to design personalised experiences, and building a distributed computing network that can render a unique version for every viewer without crashing. If successful, this would transform how public service broadcasters like the BBC create and deliver content. It could make news, drama, and sports more accessible for people with disabilities, more engaging for younger audiences, and more relevant for diverse communities. The underlying infrastructure—a hybrid network of edge computing and cloud resources—could also improve efficiency and reduce energy costs for any media streaming service.
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Personalisation of media experiences for the individual is vital for audience engagement of young and old, allowing more meaningful encounters tailored to their interest, making them part of the story, and increasing accessibility. The goal of the BBC Prosperity Partnership is to realise a transformation to future personalised content creation and delivery at scale for the public at home or on the move. Evolution of mass-media audio-visual 'broadcast' content (news, sports, music, drama) has moved increasingly towards Internet delivery, which creates exciting potential for hyper-personalised media experiences delivered at scale to mass audiences. This radical new user-centred approach to media creation and delivery has the potential to disrupt the media landscape by directly engaging individuals at the centre of their experience, rather than predefining the content as with existing media formats (radio, TV, film). This will allow a new form of user-centred media experience which dynamically adapts to the individual, their location, the media content and producer storytelling intent, together with the platform/device and the network/compute resources available for rendering the content.The BBC Prosperity Partnership will position the BBC at the forefront of this 'Personalised Media' revolution enabling the creation and delivery of new services, and positioning the UK creative industry to lead future personalised media creation and intelligent network distribution to render personalised experiences for everyone anywhere. Realisation of personalised experiences at scale presents three fundamental research challenges: capture of object-based representations of the content to enable dynamic adaption for personalisation at the point of rendering; production to create personalised experiences which enhance the perceived quality of experience for each user; and delivery at scale with intelligent utilisation of the available network, edge and device resources for mass audiences. The BBC Prosperity Partnership will address the major technical and creative challenges to delivering user-centred personalised audience experiences at scale. Advances in audio-visual AI for machine understanding of captured content will enable the automatic transformation of captured 2D video streams to an object-based media (OBM) representation. OBM will allow adaptation for efficient production, delivery and personalisation of the media experience whilst maintaining the perceived quality of the captured video content. To deliver personalised experiences to audiences of millions requires transformation of media processing and distribution architectures into a hybrid and distributed low-latency computation platform, allowing flexible deployment of compute-intensive tasks across the network. This will achieve efficiency in terms of cost and energy use, while providing optimal quality of experience for the audience within the technical constraints of the system.
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