DELVE-VIDEO: Deep-Learning based Bitstream Analytics for Value Discovery in Video

The DELVE-VIDEO project creates a robust and performant ecosystem of software tools and infrastructure components to uniquely identify and describe video attributes within networks and file systems. This establishes a foundation for content owners and service providers to protect their video assets from piracy, measure viewer traffic, and enrich asset management, rights management and recommendation services, all with substantially advanced simplicity and automation in comparison to existing methods. The project builds on novel video signature extraction technology developed by TMI/UCL (in part via Innovate UK –supported project Video Clarity) and Dithen. Deep learning methods will now be added and the signature extraction and content classification will be carried out predominantly using compressed domain information, coupled with very limited decoding. The principal aim is to enable unique semantic identification of media regardless of platform (film, television, web, OTT, mobile) or encoding characteristics. Compelling new commercial services and technology licensing opportunities will be launched by the project partners, enabling new levels of analysis and reliability for copyright protection and information services.