Transforming video content through compression and large-scale processing
The video coding team withinBBC R&Dfocuses on multiple aspects of video technology, with the general goal of supporting the delivery of high-quality content to all BBC audiences. In addition to performing core fundamental research on video compression standards, the video coding team is researching new, advanced ways of performing compression based on machine learning, artificial intelligence and content analytics, while also applying our findings to enable new content experiences.
Audiences are consuming more and more video, demanding increasingly higher quality, using a variety of devices including TVs, smartphones, tablets and computers. This is why video compression standards are needed, which allow compressed content to be distributed and then decoded by anyone – ready to be displayed on the device of choice.
In this context, research is supported by H2020 Marie Sklodowska-Curie ETN grant JOLT and UK’s EPSRC iCASE grants where researchers are also enrolled to PhD programmes at Dublin City University and Queen Mary University of London. To enable their research, access to adequate computational facilities is needed.
The use of large-scale processing resources have the capabilities to transform how content providers obtain, produce and deliver content in challenging scenarios. A move away from expensive bespoke broadcast specific facilities and hardware to more commoditised scalable-cloud based resources will enable providers to more efficiently manage its content compared to what has traditionally been achievable.
Integrate access to the EOSC compute infrastructure