Reports

Tech Paper 2019: This paper proposes deep-learning based precoding techniques for video compression that are compatible with current and future codecs, achieving significant bitrate reduction and lowering cloud encoding complexity.

Tech Papers 2019: This paper describes trials carried out by the BBC and associated partners in the areas of distribution and content generation using 5G technologies and examines the future role that 5G could have in broadcasting.

Tech Papers 2019: This paper presents a low-cost 3D system using multi-sensor fusion to create photorealistic sign language interpreter avatars for accessible broadcasting.

Tech Papers 2019: This paper presents the concept and specifications of the advanced ISDB-T system under study. The verification results of a computer simulation, and laboratory and large-scale field experiments are also described.

Tech Papers 2019: This paper summarizes the development and real-world application of an Object-Based Media toolkit, highlighting its use in interactive productions and lessons learned from collaboration with producers and audiences.

Tech Paper 2019: This paper presents our findings from the first half of 2019 of the concepts and interactions of live HDR production as they are applied to practical Broadcast Production and Contribution Systems.

Tech Papers 2019: This paper explores future AR/VR broadcasting, proposing methods to handle 2D video in AR glasses and extending formats to enhance depth and viewer presence.

Tech Papers 2019: This paper presents an AI algorithm for Globoplay that automatically selects drama series thumbnails using video, summaries, and captions, matching manual curation quality while enhancing viewer engagement.

Tech Papers 2019: This paper introduces the 5G Media Streaming Architecture (5GMSA), a modular, API-driven framework developed by 3GPP to support advanced media services—such as unicast streaming, uplink video, and XR—through collaboration between mobile network operators and third-party content providers.

Tech Papers 2019: This paper presents a decentralized, privacy-preserving collaborative recommendation architecture based on anonymous token exchanges, enabling networked personalization without centralized data control and offering an alternative to GAFA-style ecosystems.