IBC2024 Tech Papers: A user-centric approach to facial recognition for TV content

The increasing applicability of facial recognition technology (FRT) in the broadcast and media industries necessitates a standardised evaluation framework specifically designed for video content. The absence of such a framework poses challenges in the decision-making process regarding the implementation of facial recognition systems, as reliance on conventional Machine Learning (ML) metrics may lead to suboptimal choices. In fact, these metrics prioritise performance optimization, which can inadvertently overlook user-centric properties essential for practical applications and result in masking critical user-centric properties, such as the relevance and accessibility of the metadata produced.

To address this gap, the EBU has developed a benchmark tailored for facial recognition in television programming, accompanied by a state-of-the-art AI model optimised for this framework. This initiative involved the extensive annotation of a video dataset guided by user-centric metrics, which prioritise the accurate retrieval of relevant personalities in accordance with the requirements of documentalists. Our strategy improves...