Vendors are emphatic that content metadata holds myriad value for broadcasters, increasing video’s findability and searchability, tracking rights and protecting against deepfakes and using AI to make the entire process easier. Above: An example of using machine learning to identify objects in video with correlating time markers. In this way, users can search across video with increasingly sophisticated queries such as “2 Persons + 7 Cars” to show all matches across an entire content library.
Three Media, a specialist media company in workflow and technology management, has added new functionality to its flagship XEN:Pipeline software suite. The business process platform, used to manage OTT, online […]
Artificial intelligence has been touted for several years as a potential tool for cleaning up the metadata in broadcasters’ archives and making old clips more easily retrievable. COVID-19’s role in scuttling much live programming may finally push AI’s value for MAMs into the foreground.
