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Data-driven personalisation of television content: a survey

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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.

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Notes

  1. https://aimagelab.ing.unimore.it/imagelab/researchActivity.asp?idActivity=19.

  2. https://paperswithcode.com/task/semantic-segmentation.

  3. https://paperswithcode.com/sota/image-classification-on-imagenet, last accessed 1 Feb 2022.

  4. https://www.theatlantic.com/technology/archive/2021/04/artificial-intelligence-misreading-human-emotion/618696/.

  5. https://www.iti.gr/iti/projects/LinkedTV.html.

  6. https://google.github.io/mediapipe/solutions/autoflip.

  7. https://retv-project.eu/wp-content/uploads/2020/01/ReTV_D6.2_final.pdf.

  8. https://retv-project.eu/portfolio-item/dynamiccontentinsertion/.

  9. http://multimedia3.iti.gr/video_fragmentation/service/start.html.

  10. http://multimedia2.iti.gr/onlinevideoanalysis_v5/service/start.html.

  11. https://www.playment.io/.

  12. https://wikidata.org.

  13. https://www.dbpedia-spotlight.org/.

  14. https://www.bbc.co.uk/blogs/bbcinternet/2012/04/sports_dynamic_semantic.html.

  15. https://www.infoq.com/presentations/bbc-data-platform-api/.

  16. https://cloud.google.com/video-intelligence.

  17. https://vi.microsoft.com/.

  18. https://aws.amazon.com/rekognition/.

  19. https://cloud.google.com/vertex-ai/docs/start/automl-model-types#video.

  20. https://retv-project.eu/content-adaptation-publication-online/.

  21. http://multimedia2.iti.gr/videosummarization/service/start.html.

  22. https://www.vsn-tv.com/en/products/vsn-wedit/.

  23. https://www.pixop.com/blog/super-resolution-in-broadcasting.

  24. http://cognitus-h2020.eu/.

  25. http://multimedia2.iti.gr/videosmartcrop**/service/start.html.

  26. https://www.bbc.co.uk/rd/object-based-media, accessed 24 January 2022.

  27. https://www.bbc.co.uk/rd/blog/2019-04-object-based-media-click-interactivity-tv.

  28. https://ai.facebook.com/research/data2vec-a-general-framework-for-self-supervised-learning-in-speech-vision-and-language.

  29. https://blog.google/products/ads-commerce/2021-01-privacy-sandbox/.

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Acknowledgements

This work was supported by the EU’s Horizon 2020 research and innovation programme under Grant Agreements H2020-780656 ReTV and H2020-951911 AI4Media.

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  1. MODUL Technology, Vienna, Austria

    Lyndon Nixon

  2. Birmingham City University, Birmingham, England, UK

    Jeremy Foss

  3. CERTH-ITI, Thessaloníki, Greece

    Konstantinos Apostolidis & Vasileios Mezaris

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Nixon, L., Foss, J., Apostolidis, K. et al. Data-driven personalisation of television content: a survey. Multimedia Systems 28, 2193–2225 (2022). https://doi.org/10.1007/s00530-022-00926-6

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