Imagine the scene. A castle in the Scottish Highlands. Cameras rolling in glorious 4K in every room and every location just in case one of the big dog traitors or hapless faithfuls enters.
Much like many reality TV shows, those cameras are rolling and recording even when people are not in the scene, in the hope of catching the moment someone enters.
Tens of UHD cameras just rolling and recording, waiting for that moment of change.
The result? Minutes, hours or even days of static video.
Once recorded, finding that moment to edit the footage can be a painfully slow process.
Then there’s the cost of keeping all that static video, not even ‘just in case’ but through lack of choice, lack of data to drive decisions.. Thousands of hours, hundreds of terabytes of static useless footage being protected in highly redundant storage systems, potentially forever.
The same is true for:
- Sports environments – cameras recording stadiums, arenas, changing rooms and dugouts etc
- News conferences waiting for someone to hit the podium
- Wildlife documentaries waiting for that illusive Beagle shot
- Committee rooms in government buildings (might be a while waiting for action here, even when people enter the room 😉 )
All waiting for action. All waiting for a moment of change.
So how can we thin this content down to those moments that actually matter?
Aside from manually scrubbing through tens of thousands of minutes of raw footage, other options include using AI to find the moments. The problem with this is that it’s expensive and you end up sending tens of thousands of minutes of duplicate frames to the AI service of your choice. Also, it’s not great for the planet.
So how can Ad Signal Match make this process easier?
Our Match product performs proprietary fingerprinting of each frame in a video. Once we have that intelligence, we can analyse the difference between frames. Not using AI, just some hardcore but lightweight maths.
Using that data, we can guide you to where moments of change occur and help you build rules to thin the content that ends up in the archive.
We call it Content Thinning, and we’d love to show you how it works.