Industry Context
The media production industry has been transformed by the explosion of mobile devices and the growing demand for content accessible on any screen. Modern workflows must handle multiple heterogeneous sources and playout targets simultaneously, placing new strains on quality assurance and Media Asset Management (MAM).
Rich, accurate metadata and data integrity are essential for effective QA and MAM. At the time the ReCAP project was conceived, existing solutions were largely limited to enterprise-grade offerings from major broadcast manufacturers, leaving a gap for more accessible, scalable alternatives.
The ReCAP Response
ReCAP set out to develop an automatic content analysis platform that would bring real-time metadata extraction and quality control capabilities within reach of a broader range of media organisations. Co-funded by the European Union's Horizon 2020 Programme under grant agreement No 732461, the project ran through May 2018.
The platform was designed to analyse live broadcast-quality video and archive content, extracting time-stamped descriptive and technical metadata automatically. By integrating with existing MAM systems, ReCAP aimed to unlock value in historical content archives and streamline day-to-day production workflows.
Explore Further
Objectives
The goals and intended outcomes that guided the ReCAP project from inception through completion.
View Objectives →Work Plan
The structured work breakdown and timeline that shaped the project's execution.
View Work Plan →Technical Overview
Details on the platform's analysis capabilities, including logo and face detection, content duplication detection, and automatic QC monitoring.
View Technical →Consortium
Meet the four European partners — NMR, Tools On Air, Nablet, and Joanneum Research — who collaborated on the project.
View Consortium →The challenges facing modern media production extend beyond technical infrastructure into the very nature of how content is created, stored, and rediscovered. As broadcasters and creative companies accumulate vast libraries of video assets, the ability to automatically extract meaningful information from that material becomes critical. Real-time content analysis offers a pathway to unlock the value hidden in historical archives, enabling automated tagging, scene detection, and speech-to-text transcription without costly manual effort. By embedding these capabilities directly into production workflows, media organisations can dramatically improve the speed and accuracy of their metadata creation, making content more discoverable and reusable across multiple platforms and devices.