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Multimedia Systems
Erschienen in: Multimedia Systems 6/2022

23.04.2022 | Special Issue Article

Data-driven personalisation of television content: a survey

verfasst von: Lyndon Nixon, Jeremy Foss, Konstantinos Apostolidis, Vasileios Mezaris

Erschienen in: Multimedia Systems | Ausgabe 6/2022

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Abstract

This survey considers the vision of TV broadcasting where content is personalised and personalisation is data-driven, looks at the AI and data technologies making this possible and surveys the current uptake and usage of those technologies. We examine the current state-of-the-art in standards and best practices for data-driven technologies and identify remaining limitations and gaps for research and innovation. Our hope is that this survey provides an overview of the current state of AI and data-driven technologies for use within broadcasters and media organisations. It also provides a pathway to the needed research and innovation activities to fulfil the vision of data-driven personalisation of TV content.
Vorheriger Artikel Towards automatic placement of media objects in a personalised TV experience
Nächster Artikel Micro-expression recognition based on SqueezeNet and C3D

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Metadaten
Titel
Data-driven personalisation of television content: a survey
verfasst von
Lyndon Nixon
Jeremy Foss
Konstantinos Apostolidis
Vasileios Mezaris
Publikationsdatum
23.04.2022
Verlag
Springer Berlin Heidelberg
Erschienen in
Multimedia Systems / Ausgabe 6/2022
Print ISSN: 0942-4962
Elektronische ISSN: 1432-1882
DOI
https://doi.org/10.1007/s00530-022-00926-6

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Map modeling for full body gesture using flex sensor and machine learning algorithms

Special Issue Paper

Fast stereo visual odometry based on LK optical flow and ORB-SLAM2

Special Issue Paper

Understanding videos with face recognition: a complete pipeline and applications