.jpg)
Tech Papers 2018: This paper explores how AI and machine learning can automate video analysis and multicamera shot selection to expand live event coverage with minimal crew.
Abstract
In common with many industries, TV and video production is likely to be transformed by Artificial Intelligence (AI) and Machine Learning (ML), with software and algorithms assisting production tasks that, conventionally, could only be carried out by people. Expanded coverage of a diverse range of live events is particularly constrained by the relative scarcity of skilled people, and is a strong use case for AI-based automation.
Exclusive Content
This article is available with a Technical Paper Pass
.jpg)
Dynamic power control for sustainable broadcast transmitter networks
Tech Papers 2026: This paper proposes an approach that uses predictive modelling in combination with real-time interference monitoring to optimise transmitter powers dynamically, with minimal impact on the consumer.
.jpg)
AI-driven anonymisation that preserves human performance
Tech Papers 2026: This paper presents two AI-driven workflows designed to preserve emotional nuance while ensuring anonymity.
.jpg)
Search first, inspect visually when needed: A multi-agent architecture for semantic video archival retrieval
Tech Papers 2026: This paper introduces Smart Chat, a multi-agent video question-answering system that searches indexed video moments, localizes candidate evidence, and inspects a short clip only when visual verification is needed.
.jpg)
A standardised framework for C2PA provenance in media workflows
Tech Papers 2026: This paper presents the first standardised framework for implementing C2PA for media provenance across newsrooms of varying sizes and operational contexts.
Dynamic streaming content packaging with C2PA
Tech Papers 2026: This paper presents an implementation of the approach adopted by C2PA for live video to dynamic packaging.
Registered users only: Login