The aim of this research project is to develop a system which, inserted into a television automation platform, is capable to automatically identify the highlights of an input video.

The goal of this project is to be able to generate and then automatically publish the result on VOD/OTT platforms (I.E.: Website, APP, HBBTV, Social Platforms).

Highlights generally mean those passages of a video which, once identified, are able to describe the most salient moments of the original video.

The system must be able to recognize the highlights based on video topology. In case of “sport-football”, it will therefore have to recognize, for example, yellow and red cards as well as goals, while in “sport-tennis” it will have to be able to recognize the end of a set and the salient events based on the sentiment of the video.

For contents for which it is not possible to give a precise subcategory, it is therefore foreseen to recognize the salient passages based only on the sentiment of the video. Example, during a television talk show, recognize when the discussion becomes more heated.

The analysis carried out by the AI system will have to assign scores to the extrapolated sequences. The score indicates how important that particular segment is, in relation with the complete video, so as to allow the system that analyzes the result to be able to choose the best highlights.