Filling the Gaps in Video Transcoder Deployment in the Cloud

Cloud based deployment of content production and broadcast workflows has continued to disrupt the industry after the pandemic. The key tools required for unlocking cloud workflows, e.g., transcoding, metadata parsing, streaming playback, are increasingly commoditized. However, as video traffic continues to increase there is a need to consider tools which offer opportunities for further bitrate/quality gains as well as those which facilitate cloud deployment. In this paper we consider pre-processing, rate/distortion optimization and cloud cost prediction tools which are only just emerging from the research community. These tools are posed as part of the per-clip optimization approach to transcoding which has been adopted by the large streaming media processing entities but has yet to be made more widely available for the industry.

Vibhoothi | Sigmedia Group, Department of Electrical Engineering, Trinity College Dublin | Dublin 02, Ireland
Daniel Joseph Ringis | Sigmedia Group, Department of Electrical Engineering, Trinity College Dublin | Dublin 02, Ireland
Xin Shu | Sigmedia Group, Department of Electrical Engineering, Trinity College Dublin | Dublin 02, Ireland
François Pitié | Sigmedia Group, Department of Electrical Engineering, Trinity College Dublin | Dublin 02, Ireland
Zsolt Lorincz | Overcast HQ | Dublin 02, Ireland
Philippe Brodeur | Overcast HQ | Dublin 02, Ireland
Anil Kokaram | Sigmedia Group, Department of Electrical Engineering, Trinity College Dublin | Dublin 02, Ireland