Visual automation platform

Automating the reconstruction of French TV channels listings

Industry
Audiovisual
Market
French
Turnover
€37,9M
Number of employees
1250
ABOUT

INA

Founded in 1975, the National Audiovisual Institute (INA) is a public broadcasting and digital company whose main missions consist in collecting, archiving and promoting the French televisual heritage. In order to constantly innovate their users’ experience, the INA promotes its contents and shares them with as wide an audience as possible. Hence how, since 1995, its two-fold mission is separated between managing, preserving and marketing public television archives one one side and, for the sake of cultural preservation, collecting and consulting film, TV and radio legal deposits on the other.

OBJECTIVES

  • To reconstruct, sequence by sequence and day by day, French television listings. In doing so, the automation enriches and assists archivists in their indexation and classification tasks.
  • To standardize how video streams are indexed, whatever their source, format, or quality

Context

As the guardian of the French television, radio and web media archives, the INA is responsible for the proper conservation of the French audiovisual heritage, its safeguarding and its promotion to the general public, researchers and professionals. At the time of its creation, the French audiovisual landscape only included a handful of channels that were exclusively public. Since then, the INA’s scope of action has considerably expanded, as has the volume of broadcasting flows to be processed (the INA captures 184 TV and radio channels every day, and collects content from more than 15,000 social network accounts, more than 10,000 video platform accounts, and more than 5,000 podcast collections). However, in order to carry out its mission, the Institute has to deal with a technological legacy made up of different solutions that were implemented successively, in doing so gradually locking up data in “sealed” systems and thus requiring incessant manual synchronization from one database to another. This situation led, in 2014, to the implementation of a data governance strategy, based on the overhaul of its information system. This approach, aimed at centralizing and harmonizing systems, has enabled the company to initiate various data production automation projects.

Challenges

The documentary processing of media in the legal deposit currently relies on data acquired from partners, such as broadcasting companies or some agencies specialized in media monitoring.Yet these data, provided by channels, are sometimes incomplete and above all forecasted, which implies numerous verifications. In this context, the INA has been particularly interested in automating the cutting and cataloguing of TV and radio listings. The objective was to get rid of the existing technological “millefeuille” and its inherent problems (non-harmonized data, duplicates, etc.) to rely on an intelligent solution that would combine different tools. This solution had to identify the programs, but also reconstitute the daily program listings to facilitate the cataloguing and description of the collections.

The automation aims to gain autonomy in the reconstitution of program listings, to better promote the Institute’s data and to participate in the implementation of a unified and detailed access to broadcasting archives.

Solution

The INA chose to use Deepomatic’s platform to build and train its own image classification models, in order to perform a first breakdown of the programs per day. The Institute was convinced by Deepomatic’s promise: business teams could quickly become totally autonomous thanks to its solution, without having to systematically use the skills of a data scientist.

This solution first allowed for a segmentation of newscasts, automatically distinguishing between on-set images and images of reports, credits or weather forecasts. These first results made it possible to consider the analysis broadcasting days of 24H rolling news channels. In this context, the image classification offered by Deepomatic allows not only to distinguish “universal” elements such as the sets, but also “specific” elements, such as the set of a given program. Currently, the INA is planning to use Deepomatic on music variety shows and talkshows, which have more complex structures, alternating on-set passages, artistic performances, reports and interviews.

Benefits

The benefits of Deepomatic for the INA can now be seen mainly on 3 levels:

  • Time saving and optimized accuracy when cataloguing and indexing videos 
  • Contribution to the governance and enrichment strategy of the data lake in order to better valorize the data (maintain the link between the different data, enrich and link the data etc.)
  • Autonomy in both deployment and modeling thanks to a complete and intuitive interface that allows business users to easily learn how to use it

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