Evertz positions the DreamCatcher system for video production powered by real-time metadata built by AI
Partnering with ShotTracker, Ease Live uses data to automate storytelling
In an age where analytics drives decisions on the field of the largest professional sports franchises, it is only a matter of time before real-time data generated by artificial intelligence powers the creation of live content and on demand by sports broadcasters.
Evertz believes the time is right with the latest developments in its IP-based production suite, DreamCatcher.
Through a partnership with the ShotTracker sensor system and use of technology gained from Evertz’s acquisition last year of the interactive graphics platform Ease Live, Evertz is targeting the college athletics market with a platform he describes as â€œdata-driven video productionâ€.
Essentially, the system uses tracking data, a locked 4K camera (or other standalone cameras), and timecode synchronization with all the cameras in a broadcaster’s arsenal to tie everything together to create replays and organized highlight packages based on real-time metadata.
The system turns data into a tool in the arsenal of storytelling. Want to get into a game by following a player’s bounces? Set the metadata and a highlight playlist is created using the angles of the locked camera as well as all the different traditional broadcast streams that a timecode syncs into the system. Has a surprising player off the bench had a big day? Add metadata fields during or after the game, and DreamCatcher will leverage the data already collected to spit out the exact content you want.
â€œAll of that metadata, whether it’s real-time or not, adds up to the backend, where you can do live production or automated live production,â€ explains Nima Malekmanesh, Product Marketing Manager / Senior Engineer, DreamCatcher, Evertz. â€œYou can supplement and increase your production directly; your traditional proofreaders won’t have to cut the content, name it, tag it, export it. Referees would automatically see the games [in Video Assistant Refereeing] from several angles. Everything can be automated.
According to Evertz, the platform is valuable for creators of live content in three areas: highlight creation (where producers can pull data for stories), clip creation (for operators who need to focus on more than one domain when cutting reruns for live production), and automated logging and exporting to a broadcaster’s asset management software.
In the live environment, the ability to deploy the 4K camera to zoom for automated camera tracking is also a great asset. Using digital zoom, DreamCatcher can isolate and track specific player or players on command, providing replays based on predetermined scenarios from an unactuated camera. For on-demand content, automated clipping will also immediately cut, tag and record real-time playback. While syncing the locked camera source with other streaming cameras to create more dynamic replays, highlight packages, and even blend.
â€œBecause we have real-time X, Y, Z data coming in through ShotTracker, with ball tracking, I can select multiple players,â€ Malekmanesh explains. “The image will then zoom in and out, [keeping] these players of the [shot] always. It is very powerful [from the perspective of] a coach or a fan or a broadcaster. There might be a catcher versus cornerback game that you want to call. You can customize and have as many of these isos as you want.
Thanks to Ease Live, the system can also put controls in the hands of the viewer. Through streaming templates, broadcasters could offer fans the ability to tailor their own custom-made highlights packages or real-time camera tracks through live interactive graphics embedded directly into the streaming video. direct.
According to Evertz, more than 50 colleges, many in the SEC and ACC, are already DreamCatcher customers who have access to this technology. The full platform underwent its first real end-to-end test at the Big 12 Men’s Basketball Tournament in March. Currently, the platform is more naturally deployed for basketball, but the company claims football and even volleyball are not far behind as AI continues to grow smarter in these sports. .
Technology is maturing quickly, according to Evertz engineers, who note that the biggest challenges right now lie in setting up workflows on the end-user side.
“Encourage production teams to adopt a new workflow [is a challenge]Says Malekmanesh. â€œThis is where the challenges lie; the technology is actually very resilient. Make sure that schools wear the sensors, [too]. “
The technology offers very exciting prospects for a future where analytics will not only force baseball teams to make changes on the field, but dictate the methods of content creation for sports content rights holders large and small. .